Part 1 Of Set 1 And Set 2

Set 1 :

Textbook :

Principles of Incident Response and Disaster Recovery (2014). Cengage Learning. ISBN: 978-1111138059. Michael E. Whitman, Herbert J. Mattord, Andrew Green.

**NEED 300 WORDS EACH , SHOULD HAVE QUESTION INCLUDED , NEED 3 REFERENCES EACH**

• Module 1 Graded Assignment

From Chapter 1, page 37, Exercise 1.1

• Module 2 Graded Assignment

From Chapter 2, page 81, Exercise 2.2

• Module 3 Graded Assignment

From Chapter 3, page 123, Exercise 3.1, 3.2

• Module 4 Graded Assignment

From Chapter 4, page 156, Exercise 4.1, 4.2, 4.3, 4.4

Set 2 :

***WILL CONFIRM THE TEXTBOOK IN 12 HOURS , DO NOT START SET 2 UNTIL I CONFIRM THE TEXT BOOK***

**NEED 300 WORDS EACH , SHOULD HAVE QUESTION INCLUDED , NEED 3 REFERENCES EACH**

Week 1:

From Chapter 1, page 37, Real World Exercise 1.1

Week 2:

From Chapter 2, page 81, Real World Exercise 2.2

Week 3:

From Chapter 3, page 123, Real World Exercise 3.1 and 3.2

Week 4:

From Chapter 4, page 156, Real World Exercise 4.1, 4.2, 4.3, and 4.4

 
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Excel 2019 In Practice – Ch 3 Independent Project 3-4

Q2&Q3

Classic Gardens and Landscapes (CGL)
Revenue for Quarters 2 and 3
Revenue Categories April May June July August September Total
Lawn Maintenance $7,660.13 $7,741.13 $7,886.48 $7,650.23 $7,683.30 $8,094.38 $46,715.63
Tree & Shrubbery $11,819.93 $11,909.48 $12,043.13 $11,803.28 $11,879.78 $12,226.28 $71,681.85
Patio and Furniture $15,192.23 $13,070.48 $12,957.30 $13,039.88 $15,318.23 $16,876.13 $86,454.23
Fountains and Irrigation $4,478.18 $4,708.13 $4,475.25 $5,153.63 $5,514.53 $7,919.55 $32,249.25
Design Consulting $579.38 $585.23 $631.13 $563.18 $584.78 $698.40 $3,642.08
Total Revenue $39,729.83 $38,014.43 $37,993.28 $38,210.18 $40,980.60 $45,814.73 $240,743.03

 

() Print Info

Student Name: Gullickson, Finn

Student ID: D41122036

Username: D41122036 Excel 2019 In Practice – Ch 3 Independent Project 3-4 COURSE NAME BIS155 SEP20 Master | Data Analysis with Spreadsheets with Lab – 11964

Start Date: 09/05/2011:59 PMUS/Mountain Due Date: 09/13/2011:59 PMUS/Mountain End Date: 10/25/2011:59 PMUS/Mountain

Independent Project 3-4 For this project, you create a column chart to illustrate April–September revenue for Classic Gardens and Landscapes. You also build a pie chart sheet to graph the proportion that each category contributes to total revenue. [Student Learning Outcomes 3.1, 3.2, 3.3, 3.4, 3.5, 3.6]

File Needed: ClassicGardens-03.xlsx (Available from the Start File link.) Completed Project File Name: [your name]-ClassicGardens-03.xlsx

Skills Covered in This Project Create a chart object. Size and position a chart object. Edit and format chart elements. Edit the source data for a chart. Build a pie chart sheet. Use texture as fill. Add and format data labels in a chart.

This image appears when a project instruction has changed to accommodate an update to Microsoft 365 Apps. If the instruction does not match your version of Office, try using the alternate instruction instead.

1. Open the ClassicGardens-03.xlsx start file. If the workbook opens in Protected View, click the Enable Editing button so you can modify it. The file will be renamed automatically to include your name. Change the project file name if directed to do so by your instructor, and save it.

NOTE: If group titles are not visible on your Ribbon in Excel for Mac, click the Excel menu and select Preferences to open the Excel Preferences dialog box. Click the View button and check the Group Titles check box under In Ribbon, Show. Close the Excel Preferences dialog box.

2. Create a Clustered Column chart object for cells A4:G9.

3. Move the chart object so that its top-left corner is at cell A12. Size the bottom of the chart to reach cell H30.

4. Edit the chart title to display CGL Major Sales Revenue and press return. On the second line, type Second and Third Quarters.

SIMnet – Excel 2019 In Practice – Ch 3 Independent Project 3-4 https://devry.simnetonline.com/sp/embed/#pr/5573828

1 of 3 10/23/20, 12:00 PM

 

 

Figure 3-71 Resize the chart by dragging the resize pointer

5. Apply chart Style 14 to the chart.

6. Format the first line and the second line of the chart title to a font size of 20 pt.

7. Apply a 1 pt Black, Text 1 (second column) outline to the chart area.

8. Verify that the chart is still selected. In the highlighted range in the worksheet, drag the resize pointer to remove the Design Consulting data series from the chart (Figure 3-71).

9. Create a 3-D Pie chart sheet for cells A4:A9 and cells H4:H9. Move the chart to its own sheet named Revenue Breakdown. Hint: Use the Move Chart button [Chart Design tab, Location group].

10. Edit the chart title to display Revenue by Category. Change the font size to 32.

11. Select the legend and change the font size to 12.

12. Apply the Woven mat texture fill (first row, fourth column) to the Patio and Furniture slice.

13. Select the pie shape and add data labels to display in the center of each slice.

a. Display the Format Data Labels task pane, choose the Accounting format [Label Options button, Number group], and set 0 decimal places.

b. Change the data label font size to 14 pt and apply bold [Home tab, Font group].

14. Deselect the chart.

15. Save and close the workbook (Figure 3-72).

Figure 3-72 Excel 3-4 completed worksheet and chart

16. Upload and save your project file.

17. Submit project for grading.

SIMnet – Excel 2019 In Practice – Ch 3 Independent Project 3-4 https://devry.simnetonline.com/sp/embed/#pr/5573828

2 of 3 10/23/20, 12:00 PM

 

 

SIMnet – Excel 2019 In Practice – Ch 3 Independent Project 3-4 https://devry.simnetonline.com/sp/embed/#pr/5573828

3 of 3 10/23/20, 12:00 PM

 
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Cloud Computing

About This eBook

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optimize the presentation of these elements, view the eBook in single-column, landscape mode and adjust the font size to the smallest setting. In addition to presenting code and configurations in the reflowable text format, we have included images of the code that mimic the presentation found in the print book; therefore, where the reflowable format may compromise the presentation of the code listing, you will see a “Click here to view code image” link. Click the link to view the print-fidelity code image. To return to the previous page viewed, click the Back button on your device or app.

 

 

Cloud Computing Concepts, Technology & Architecture

Thomas Erl, Zaigham Mahmood, and Ricardo Puttini

Upper Saddle River, NJ • Boston • Indianapolis • San Francisco New York • Toronto • Montreal • London • Munich • Paris • Madrid

Cape Town • Sydney • Tokyo • Singapore • Mexico City

 

 

Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and the publisher was aware of a trademark claim, the designations have been printed with initial capital letters or in all capitals.

The authors and publisher have taken care in the preparation of this book, but make no expressed or implied warranty of any kind and assume no responsibility for errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of the use of the information or programs contained herein.

The publisher offers excellent discounts on this book when ordered in quantity for bulk purchases or special sales, which may include electronic versions and/or custom covers and content particular to your business, training goals, marketing focus, and branding interests. For more information, please contact:

U.S. Corporate and Government Sales (800) 382-3419 corpsales@pearsontechgroup.com

For sales outside the United States, please contact:

International Sales international@pearsoned.com

Visit us on the Web: informit.com/ph

The Library of Congress Cataloging-in-Publication data is on file.

Copyright © 2013 Arcitura Education Inc.

All rights reserved. Printed in the United States of America. This publication is protected by copyright, and permission must be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. To obtain permission to use material from this work, please submit a written request to Pearson Education, Inc., Permissions Department, One Lake Street, Upper Saddle River, New Jersey 07458, or you may fax your request to (201) 236-3290.

ISBN-13: 978-0-13-338752-0 ISBN-10: 0-13-338752-6

Text printed in the United States on recycled paper at Courier in Westford,

 

 

Massachusetts.

First printing: May 2013

Editor-in-Chief Mark L. Taub

Managing Editor Kristy Hart

Senior Project Editor Betsy Gratner

Copy Editor and Development Editor Maria Lee

Senior Indexer Cheryl Lenser

Proofreaders Maria Lee Williams Woods Publishing

Publishing Coordinator Kim Boedigheimer

Research Assistant Briana Lee

Cover Designer Thomas Erl

Compositor Bumpy Design

Photos Thomas Erl Dominika Sládkovičová

Graphics KK Lui Briana Lee

 

 

Readers can download high-resolution, full-color versions of all this book’s figures at

www.informit.com/title/9780133387520

and

www.servicetechbooks.com/cloud.

 

 

Praise for this Book

“Cloud computing, more than most disciplines in IT, suffers from too much talk and not enough practice. Thomas Erl has written a timely book that condenses the theory and buttresses it with real-world examples that demystify this important technology. An important guidebook for your journey into the cloud.”

—Scott Morrison, Chief Technology Officer, Layer 7 Technologies

“An excellent, extremely well-written, lucid book that provides a comprehensive picture of cloud computing, covering multiple dimensions of the subject. The case studies presented in the book provide a real-world, practical perspective on leveraging cloud computing in an organization. The book covers a wide range of topics, from technology aspects to the business value provided by cloud computing. This is the best, most comprehensive book on the subject—a must-read for any cloud computing practitioner or anyone who wants to get an in-depth picture of cloud computing concepts and practical implementation.”

—Suzanne D’Souza, SOA/BPM Practice Lead, KBACE Technologies

“This book offers a thorough and detailed description of cloud computing concepts, architectures, and technologies. It serves as a great reference for both newcomers and experts and is a must-read for any IT professional interested in cloud computing.”

—Andre Tost, Senior Technical Staff Member, IBM Software Group

“This is a great book on the topic of cloud computing. It is impressive how the content spans from taxonomy, technology, and architectural concepts to important business considerations for cloud adoption. It really does provide a holistic view to this technology paradigm.”

—Kapil Bakshi, Architecture and Strategy, Cisco Systems Inc.

“I have read every book written by Thomas Erl and Cloud Computing is another excellent publication and demonstration of Thomas Erl’s rare ability to take the most complex topics and provide critical core concepts and technical information in a logical and understandable way.”

 

 

—Melanie A. Allison, Principal, Healthcare Technology Practice, Integrated Consulting Services

“Companies looking to migrate applications or infrastructure to the cloud are often misled by buzzwords and industry hype. This work cuts through the hype and provides a detailed look, from investigation to contract to implementation to termination, at what it takes for an organization to engage with cloud service providers. This book really lays out the benefits and struggles with getting a company to an IaaS, PaaS, or SaaS solution.”

—Kevin Davis, Ph.D., Solutions Architect

“Thomas, in his own distinct and erudite style, provides a comprehensive and a definitive book on cloud computing. Just like his previous masterpiece, Service-Oriented Architecture: Concepts, Technology, and Design, this book is sure to engage CxOs, cloud architects, and the developer community involved in delivering software assets on the cloud. Thomas and his authoring team have taken great pains in providing great clarity and detail in documenting cloud architectures, cloud delivery models, cloud governance, and economics of cloud, without forgetting to explain the core of cloud computing that revolves around Internet architecture and virtualization. As a reviewer for this outstanding book, I must admit I have learned quite a lot while reviewing the material. A ‘must have’ book that should adorn everybody’s desk!”

—Vijay Srinivasan, Chief Architect – Technology, Cognizant Technology Solutions

“This book provides comprehensive and descriptive vendor-neutral coverage of cloud computing technology, from both technical and business aspects. It provides a deep-down analysis of cloud architectures and mechanisms that capture the real-world moving parts of cloud platforms. Business aspects are elaborated on to give readers a broader perspective on choosing and defining basic cloud computing business models. Thomas Erl’s Cloud Computing: Concepts, Technology & Architecture is an excellent source of knowledge of fundamental and in- depth coverage of cloud computing.”

—Masykur Marhendra Sukmanegara, Communication Media & Technology, Consulting Workforce Accenture

 

 

“The richness and depth of the topics discussed are incredibly impressive. The depth and breadth of the subject matter are such that a reader could become an expert in a short amount of time.”

—Jamie Ryan, Solutions Architect, Layer 7 Technologies

“Demystification, rationalization, and structuring of implementation approaches have always been strong parts in each and every one of Thomas Erl’s books. This book is no exception. It provides the definitive, essential coverage of cloud computing and, most importantly, presents this content in a very comprehensive manner. Best of all, this book follows the conventions of the previous service technology series titles, making it read like a natural extension of the library. I strongly believe that this will be another bestseller from one of the top-selling IT authors of the past decade.”

—Sergey Popov, Senior Enterprise Architect SOA/Security, Liberty Global International

“A must-read for anyone involved in cloud design and decision making! This insightful book provides in-depth, objective, vendor-neutral coverage of cloud computing concepts, architecture models, and technologies. It will prove very valuable to anyone who needs to gain a solid understanding of how cloud environments work and how to design and migrate solutions to clouds.”

—Gijs in ’t Veld, Chief Architect, Motion10

“A reference book covering a wide range of aspects related to cloud providers and cloud consumers. If you would like to provide or consume a cloud service and need to know how, this is your book. The book has a clear structure to facilitate a good understanding of the various concepts of cloud.”

—Roger Stoffers, Solution Architect

“Cloud computing has been around for a few years, yet there is still a lot of confusion around the term and what it can bring to developers and deployers alike. This book is a great way of finding out what’s behind the cloud, and not in an abstract or high-level manner: It dives into all of the details that you’d need to know in order to plan for developing applications on cloud and what to look for when using applications or

 

 

services hosted on a cloud. There are very few books that manage to capture this level of detail about the evolving cloud paradigm as this one does. It’s a must for architects and developers alike.”

—Dr. Mark Little, Vice President, Red Hat

“This book provides a comprehensive exploration of the concepts and mechanics behind clouds. It’s written for anyone interested in delving into the details of how cloud environments function, how they are architected, and how they can impact business. This is the book for any organization seriously considering adopting cloud computing. It will pave the way to establishing your cloud computing roadmap.”

—Damian Maschek, SOA Architect, Deutsche Bahn

“One of the best books on cloud computing I have ever read. It is complete yet vendor technology neutral and successfully explains the major concepts in a well-structured and disciplined way. It goes through all the definitions and provides many hints for organizations or professionals who are approaching and/or assessing cloud solutions. This book gives a complete list of topics playing fundamental roles in the cloud computing discipline. It goes through a full list of definitions very clearly stated. Diagrams are simple to understand and self-contained. Readers with different skill sets, expertise, and backgrounds will be able to understand the concepts seamlessly.”

—Antonio Bruno, Infrastructure and Estate Manager, UBS AG

“Cloud Computing: Concepts, Technology & Architecture is a comprehensive book that focuses on what cloud computing is really all about…. This book will become the foundation on which many organizations will build successful cloud adoption projects. It is a must- read reference for both IT infrastructure and application architects interested in cloud computing or involved in cloud adoption projects. It contains extremely useful and comprehensive information for those who need to build cloud-based architectures or need to explain it to customers thinking about adopting cloud computing technology in their organization.”

—Johan Kumps, SOA Architect, RealDolmen

“This book defines the basic terminology and patterns for the topic—a

 

 

useful reference for the cloud practitioner. Concepts from multitenancy to hypervisor are presented in a succinct and clear manner. The underlying case studies provide wonderful real-worldness.”

—Dr. Thomas Rischbeck, Principal Architect, ipt

“The book provides a good foundation to cloud services and issues in cloud service design. Chapters highlight key issues that need to be considered in learning how to think in cloud technology terms; this is highly important in today’s business and technology environments where cloud computing plays a central role in connecting user services with virtualized resources and applications.”

—Mark Skilton, Director, Office of Strategy and Technology, Global Infrastructure Services, Capgemini

“The book is well organized and covers basic concepts, technologies, and business models about cloud computing. It defines and explains a comprehensive list of terminologies and glossaries about cloud computing so cloud computing experts can speak and communicate with the same set of standardized language. The book is easy to understand and consistent with early published books from Thomas Erl…. It is a must-read for both beginners and experienced professionals.”

—Jian “Jeff” Zhong, Chief Technology Officer (Acting) and Chief Architect for SOA and Cloud Computing, Futrend Technology Inc.

“Students of the related specialties can fulfill their educational process with very easily understood materials that are broadly illustrated and clearly described. Professors of different disciplines, from business analysis to IT implementation—even legal and financial monitoring— can use the book as an on-table lecturing manual. IT specialists of all ranks and fields of application will find the book as a practical and useful support for sketching solutions unbound to any particular vendor or brand.”

—Alexander Gromoff, Director of Science & Education, Center of Information Control Technologies, Chairman of BPM Chair in Business Informatics Department, National Research University

“Higher School of Economics”

“Cloud Computing: Concepts, Technology & Architecture is a

 

 

comprehensive compendium of all the relevant information about the transformative cloud technology. Erl’s latest title concisely and clearly illustrates the origins and positioning of the cloud paradigm as the next- generation computing model. All the chapters are carefully written and arranged in an easy-to-understand manner. This book will be immeasurably beneficial for business and IT professionals. It is set to shake up and help organize the world of cloud computing.”

—Pethuru Raj, Ph.D., Enterprise Architecture Consultant, Wipro

“A cloud computing book that will stand out and survive the test of time, even in one of the fastest evolving areas of technology. This book does a great job breaking down the high level of complexity of cloud computing into easy-to-understand pieces. It goes beyond the basic, often repeated, explanations. It examines the fundamental concepts and the components, as well as the mechanisms and architectures that make up cloud computing environments. The approach gradually builds the reader’s understanding from the ground up. “In a rapidly evolving area like cloud computing, it’s easy to focus on details and miss the big picture. The focus on concepts and architectural models instead of vendor-specific details allows readers to quickly gain essential knowledge of complex topics. The concepts come together in the last part of the book, which should be required reading for any decision maker evaluating when and how to start a transition to cloud computing. Its thorough, comprehensive coverage of fundamentals and advanced topics makes the book a valuable resource to keep on your desk or your eBook reader, regardless if you’re new to the topic or you already have cloud experience.

“I highly recommend the book to those looking to implement or evaluate cloud environments, or simply looking to educate themselves in a field that will shape IT over the next decade.”

—Christoph Schittko, Principal Technology Strategist & Cloud Solution Director, Microsoft

“Cloud Computing: Concepts, Technology & Architecture is an excellent resource for IT professionals and managers who want to learn and understand cloud computing, and who need to select or build cloud systems and solutions. It lays the foundation for cloud concepts, models,

 

 

technologies, and mechanisms. As the book is vendor-neutral, it will remain valid for many years. We will recommend this book to Oracle customers, partners, and users for their journey toward cloud computing. This book has the potential to become the basis for a cloud computing manifesto, comparable to what was accomplished with the SOA manifesto.” —Jürgen Kress, Fusion Middleware Partner Adoption, Oracle EMEA

 

 

To my family and friends —Thomas Erl

To Zoya, Hanya, and Ozair with love —Zaigham Mahmood

To Silvia, Luiza, Isadora, and Lucas —Ricardo Puttini

 

 

Contents at a Glance

Foreword

Chapter 1: Introduction

Chapter 2: Case Study Background

Part I: Fundamental Cloud Computing

Chapter 3: Understanding Cloud Computing

Chapter 4: Fundamental Concepts and Models

Chapter 5: Cloud-Enabling Technology

Chapter 6: Fundamental Cloud Security

Part II: Cloud Computing Mechanisms

Chapter 7: Cloud Infrastructure Mechanisms

Chapter 8: Specialized Cloud Mechanisms

Chapter 9: Cloud Management Mechanisms

Chapter 10: Cloud Security Mechanisms

Part III: Cloud Computing Architecture

Chapter 11: Fundamental Cloud Architectures

Chapter 12: Advanced Cloud Architectures

Chapter 13: Specialized Cloud Architectures

Part IV: Working with Clouds

Chapter 14: Cloud Delivery Model Considerations

Chapter 15: Cost Metrics and Pricing Models

Chapter 16: Service Quality Metrics and SLAs

 

 

Part V: Appendices

Appendix A: Case Study Conclusions

Appendix B: Industry Standards Organizations

Appendix C: Mapping Mechanisms to Characteristics

Appendix D: Data Center Facilities (TIA-942)

Appendix E: Emerging Technologies

Appendix F: Cloud Provisioning Contracts

Appendix G: Cloud Business Case Template

About the Authors

About the Foreword Contributor

About the Contributors

Index

 

 

Contents

Foreword

Acknowledgments

Chapter 1: Introduction 1.1 Objectives of This Book 1.2 What This Book Does Not Cover 1.3 Who This Book Is For 1.4 How This Book Is Organized

Part I: Fundamental Cloud Computing Chapter 3: Understanding Cloud Computing Chapter 4: Fundamental Concepts and Models Chapter 5: Cloud-Enabling Technology Chapter 6: Fundamental Cloud Security

Part II: Cloud Computing Mechanisms Chapter 7: Cloud Infrastructure Mechanisms Chapter 8: Specialized Cloud Mechanisms Chapter 9: Cloud Management Mechanisms Chapter 10: Cloud Security Mechanisms

Part III: Cloud Computing Architecture Chapter 11: Fundamental Cloud Architectures Chapter 12: Advanced Cloud Architectures Chapter 13: Specialized Cloud Architectures

Part IV: Working with Clouds Chapter 14: Cloud Delivery Model Considerations Chapter 15: Cost Metrics and Pricing Models Chapter 16: Service Quality Metrics and SLAs

Part V: Appendices Appendix A: Case Study Conclusions Appendix B: Industry Standards Organizations

 

 

Appendix C: Mapping Mechanisms to Characteristics Appendix D: Data Center Facilities (TIA-942) Appendix E: Emerging Technologies Appendix F: Cloud Provisioning Contracts Appendix G: Cloud Business Case Template

1.5 Conventions Symbols and Figures Summary of Key Points

1.6 Additional Information Updates, Errata, and Resources (www.servicetechbooks.com) Referenced Specifications (www.servicetechspecs.com) The Service Technology Magazine (www.servicetechmag.com) International Service Technology Symposium (www.servicetechsymposium.com) What Is Cloud? (www.whatiscloud.com) What Is REST? (www.whatisrest.com) Cloud Computing Design Patterns (www.cloudpatterns.org) Service-Orientation (www.serviceorientation.com) CloudSchool.com™ Certified Cloud (CCP) Professional (www.cloudschool.com) SOASchool.com® SOA Certified (SOACP) Professional (www.soaschool.com) Notification Service

Chapter 2: Case Study Background 2.1 Case Study #1: ATN

Technical Infrastructure and Environment Business Goals and New Strategy Roadmap and Implementation Strategy

2.2 Case Study #2: DTGOV Technical Infrastructure and Environment Business Goals and New Strategy

 

 

Roadmap and Implementation Strategy 2.3 Case Study #3: Innovartus Technologies Inc.

Technical Infrastructure and Environment Business Goals and Strategy Roadmap and Implementation Strategy

Part I: Fundamental Cloud Computing

Chapter 3: Understanding Cloud Computing 3.1 Origins and Influences

A Brief History Definitions Business Drivers Capacity Planning Cost Reduction Organizational Agility

Technology Innovations Clustering Grid Computing Virtualization Technology Innovations vs. Enabling Technologies

3.2 Basic Concepts and Terminology Cloud IT Resource On-Premise Cloud Consumers and Cloud Providers Scaling Horizontal Scaling Vertical Scaling

Cloud Service Cloud Service Consumer

3.3 Goals and Benefits

 

 

Reduced Investments and Proportional Costs Increased Scalability Increased Availability and Reliability

3.4 Risks and Challenges Increased Security Vulnerabilities Reduced Operational Governance Control Limited Portability Between Cloud Providers Multi-Regional Compliance and Legal Issues

Chapter 4: Fundamental Concepts and Models 4.1 Roles and Boundaries

Cloud Provider Cloud Consumer Cloud Service Owner Cloud Resource Administrator Additional Roles Organizational Boundary Trust Boundary

4.2 Cloud Characteristics On-Demand Usage Ubiquitous Access Multitenancy (and Resource Pooling) Elasticity Measured Usage Resiliency

4.3 Cloud Delivery Models Infrastructure-as-a-Service (IaaS) Platform-as-a-Service (PaaS) Software-as-a-Service (SaaS) Comparing Cloud Delivery Models Combining Cloud Delivery Models IaaS + PaaS

 

 

IaaS + PaaS + SaaS 4.4 Cloud Deployment Models

Public Clouds Community Clouds Private Clouds Hybrid Clouds Other Cloud Deployment Models

Chapter 5: Cloud-Enabling Technology 5.1 Broadband Networks and Internet Architecture

Internet Service Providers (ISPs) Connectionless Packet Switching (Datagram Networks) Router-Based Interconnectivity Physical Network Transport Layer Protocol Application Layer Protocol

Technical and Business Considerations Connectivity Issues Network Bandwidth and Latency Issues Cloud Carrier and Cloud Provider Selection

5.2 Data Center Technology Virtualization Standardization and Modularity Automation Remote Operation and Management High Availability Security-Aware Design, Operation, and Management Facilities Computing Hardware Storage Hardware Network Hardware Carrier and External Networks Interconnection

 

 

Web-Tier Load Balancing and Acceleration LAN Fabric SAN Fabric NAS Gateways

Other Considerations 5.3 Virtualization Technology

Hardware Independence Server Consolidation Resource Replication Operating System-Based Virtualization Hardware-Based Virtualization Virtualization Management Other Considerations

5.4 Web Technology Basic Web Technology Web Applications

5.5 Multitenant Technology 5.6 Service Technology

Web Services REST Services Service Agents Service Middleware

5.7 Case Study Example

Chapter 6: Fundamental Cloud Security 6.1 Basic Terms and Concepts

Confidentiality Integrity Authenticity Availability Threat Vulnerability

 

 

Risk Security Controls Security Mechanisms Security Policies

6.2 Threat Agents Anonymous Attacker Malicious Service Agent Trusted Attacker Malicious Insider

6.3 Cloud Security Threats Traffic Eavesdropping Malicious Intermediary Denial of Service Insufficient Authorization Virtualization Attack Overlapping Trust Boundaries

6.4 Additional Considerations Flawed Implementations Security Policy Disparity Contracts Risk Management

6.5 Case Study Example

Part II: Cloud Computing Mechanisms

Chapter 7: Cloud Infrastructure Mechanisms 7.1 Logical Network Perimeter

Case Study Example 7.2 Virtual Server

Case Study Example 7.3 Cloud Storage Device

Cloud Storage Levels

 

 

Network Storage Interfaces Object Storage Interfaces Database Storage Interfaces Relational Data Storage Non-Relational Data Storage

Case Study Example 7.4 Cloud Usage Monitor

Monitoring Agent Resource Agent Polling Agent Case Study Example

7.5 Resource Replication Case Study Example

7.6 Ready-Made Environment Case Study Example

Chapter 8: Specialized Cloud Mechanisms 8.1 Automated Scaling Listener

Case Study Example 8.2 Load Balancer

Case Study Example 8.3 SLA Monitor

Case Study Example SLA Monitor Polling Agent SLA Monitoring Agent

8.4 Pay-Per-Use Monitor Case Study Example

8.5 Audit Monitor Case Study Example

8.6 Failover System Active-Active Active-Passive

 

 

Case Study Example 8.7 Hypervisor

Case Study Example 8.8 Resource Cluster

Case Study Example 8.9 Multi-Device Broker

Case Study Example 8.10 State Management Database

Case Study Example

Chapter 9: Cloud Management Mechanisms 9.1 Remote Administration System

Case Study Example 9.2 Resource Management System

Case Study Example 9.3 SLA Management System

Case Study Example 9.4 Billing Management System

Case Study Example

Chapter 10: Cloud Security Mechanisms 10.1 Encryption

Symmetric Encryption Asymmetric Encryption Case Study Example

10.2 Hashing Case Study Example

10.3 Digital Signature Case Study Example

10.4 Public Key Infrastructure (PKI) Case Study Example

10.5 Identity and Access Management (IAM)

 

 

Case Study Example 10.6 Single Sign-On (SSO)

Case Study Example 10.7 Cloud-Based Security Groups

Case Study Example 10.8 Hardened Virtual Server Images

Case Study Example

Part III: Cloud Computing Architecture

Chapter 11: Fundamental Cloud Architectures 11.1 Workload Distribution Architecture 11.2 Resource Pooling Architecture 11.3 Dynamic Scalability Architecture 11.4 Elastic Resource Capacity Architecture 11.5 Service Load Balancing Architecture 11.6 Cloud Bursting Architecture 11.7 Elastic Disk Provisioning Architecture 11.8 Redundant Storage Architecture 11.9 Case Study Example

Chapter 12: Advanced Cloud Architectures 12.1 Hypervisor Clustering Architecture 12.2 Load Balanced Virtual Server Instances Architecture 12.3 Non-Disruptive Service Relocation Architecture 12.4 Zero Downtime Architecture 12.5 Cloud Balancing Architecture 12.6 Resource Reservation Architecture 12.7 Dynamic Failure Detection and Recovery Architecture 12.8 Bare-Metal Provisioning Architecture 12.9 Rapid Provisioning Architecture 12.10 Storage Workload Management Architecture

 

 

12.11 Case Study Example

Chapter 13: Specialized Cloud Architectures 13.1 Direct I/O Access Architecture 13.2 Direct LUN Access Architecture 13.3 Dynamic Data Normalization Architecture 13.4 Elastic Network Capacity Architecture 13.5 Cross-Storage Device Vertical Tiering Architecture 13.6 Intra-Storage Device Vertical Data Tiering Architecture 13.7 Load Balanced Virtual Switches Architecture 13.8 Multipath Resource Access Architecture 13.9 Persistent Virtual Network Configuration Architecture 13.10 Redundant Physical Connection for Virtual Servers Architecture 13.11 Storage Maintenance Window Architecture

Part IV: Working with Clouds

Chapter 14: Cloud Delivery Model Considerations 14.1 Cloud Delivery Models: The Cloud Provider Perspective

Building IaaS Environments Data Centers Scalability and Reliability Monitoring Security

Equipping PaaS Environments Scalability and Reliability Monitoring Security

Optimizing SaaS Environments Security

14.2 Cloud Delivery Models: The Cloud Consumer Perspective Working with IaaS Environments IT Resource Provisioning Considerations

 

 

Working with PaaS Environments IT Resource Provisioning Considerations

Working with SaaS Services 14.3 Case Study Example

Chapter 15: Cost Metrics and Pricing Models 15.1 Business Cost Metrics

Up-Front and On-Going Costs Additional Costs Case Study Example Product Catalog Browser On-Premise Up-Front Costs On-Premise On-Going Costs Cloud-Based Up-Front Costs Cloud-Based On-Going Costs

Client Database On-Premise Up-Front Costs On-Premise On-Going Costs Cloud-Based Up-Front Costs Cloud-Based On-Going Costs

15.2 Cloud Usage Cost Metrics Network Usage Inbound Network Usage Metric Outbound Network Usage Metric Intra-Cloud WAN Usage Metric

Server Usage On-Demand Virtual Machine Instance Allocation Metric Reserved Virtual Machine Instance Allocation Metric

Cloud Storage Device Usage On-Demand Storage Space Allocation Metric I/O Data Transferred Metric

Cloud Service Usage

 

 

Application Subscription Duration Metric Number of Nominated Users Metric Number of Transactions Users Metric

15.3 Cost Management Considerations Pricing Models Additional Considerations Case Study Example Virtual Server On-Demand Instance Allocation Virtual Server Reserved Instance Allocation Cloud Storage Device WAN Traffic

Chapter 16: Service Quality Metrics and SLAs 16.1 Service Quality Metrics

Service Availability Metrics Availability Rate Metric Outage Duration Metric

Service Reliability Metrics Mean-Time Between Failures (MTBF) Metric Reliability Rate Metric

Service Performance Metrics Network Capacity Metric Storage Device Capacity Metric Server Capacity Metric Web Application Capacity Metric Instance Starting Time Metric Response Time Metric Completion Time Metric

Service Scalability Metrics Storage Scalability (Horizontal) Metric Server Scalability (Horizontal) Metric Server Scalability (Vertical) Metric

 

 

Service Resiliency Metrics Mean-Time to Switchover (MTSO) Metric Mean-Time System Recovery (MTSR) Metric

16.2 Case Study Example 16.3 SLA Guidelines 16.4 Case Study Example

Scope and Applicability Service Quality Guarantees Definitions Usage of Financial Credits SLA Exclusions

Part V: Appendices

Appendix A: Case Study Conclusions

A.1 ATN A.2 DTGOV A.3 Innovartus

Appendix B: Industry Standards Organizations

B.1 National Institute of Standards and Technology (NIST) B.2 Cloud Security Alliance (CSA) B.3 Distributed Management Task Force (DMTF) B.4 Storage Networking Industry Association (SNIA) B.5 Organization for the Advancement of Structured Information Standards (OASIS) B.6 The Open Group B.7 Open Cloud Consortium (OCC) B.8 European Telecommunications Standards Institute (ETSI) B.9 Telecommunications Industry Association (TIA) B.10 Liberty Alliance B.11 Open Grid Forum (OGF)

 

 

Appendix C: Mapping Mechanisms to Characteristics

Appendix D: Data Center Facilities (TIA-942)

D.1 Primary Rooms Electrical Room Mechanical Room Storage and Staging Offices, Operations Center, and Support Telecommunications Entrance Computer Room

D.2 Environmental Controls External Electrical Power Provider Interconnection Power Distribution Uninterruptible Power Source (UPS) Power Engine-Generator

D.3 Infrastructure Redundancy Summary

Appendix E: Emerging Technologies

E.1 Autonomic Computing E.2 Grid Computing

Service Grids

Appendix F: Cloud Provisioning Contracts

F.1 Cloud Provisioning Contract Structure Terms of Service Service Usage Policy Security and Privacy Policy Warranties and Liabilities Rights and Responsibilities Termination and Renewal

Specifications and SLAs Pricing and Billing Other Issues

 

 

Legal and Compliance Issues Auditability and Accountability Changes in the Contract Terms and Conditions

F.2 Cloud Provider Selection Guidelines Cloud Provider Viability

Appendix G: Cloud Business Case Template

G.1 Business Case Identification G.2 Business Needs G.3 Target Cloud Environment G.4 Technical Issues G.5 Economic Factors

About the Authors Thomas Erl Zaigham Mahmood Ricardo Puttini

About the Foreword Contributor Pamela J. Wise-Martinez, MSc

About the Contributors Gustavo Azzolin, BSc, MSc Amin Naserpour Vinícius Pacheco, MSc Matthias Ziegler

Index

 

 

Foreword by Pamela J. Wise-Martinez

The idea of cloud computing isn’t new, or overly complicated from a technology resources and internetworking perspective. What’s new is the growth and maturity of cloud computing methods, and strategies that enable the goals of business agility. Looking back, the phrase “utility computing” didn’t captivate or create the stir in the information industry as the term “cloud computing” has in recent years. Nevertheless, appreciation of readily available resources has arrived and the utilitarian or servicing features are what are at the heart of outsourcing the access of information technology resources and services. In this light, cloud computing represents a flexible, cost-effective, and proven delivery platform for business and consumer information services over the Internet. Cloud computing has become an industry game changer as businesses and information technology leaders realize the potential in combining and sharing computing resources as opposed to building and maintaining them. There’s seemingly no shortage of views regarding the benefits of cloud computing nor is there a shortage of vendors willing to offer services in either open source or promising commercial solutions. Beyond the hype, there are many aspects of the cloud that have earned new consideration due to their increased service capability and potential efficiencies. The ability to demonstrate transforming results in cloud computing to resolve traditional business problems using information technology management best practices now exists. In the case of economic impacts, the principle of pay-as-you-go and computer agnostic services are concepts ready for prime time. We can measure performance as well as calculate the economic and environmental effects of cloud computing today. The architectural change from client-server to service orientation led to an evolution of composable and reusable code; though the practice had been around for many years, it is now the de facto approach used to lower cost and identify best practices and patterns for increasing business agility. This has advanced the computer software industry’s design methods, components, and engineering. Comparatively, the wide acceptance and adoption of cloud computing is revolutionizing information and technology resource management. We now have the ability to outsource hardware and software capabilities on a large-scale to fulfill end-to-end business automation requirements. Marks and Lozano understood this emergence and the need for better software design: “…we now have the ability to collect, transport, process, store, and access data nearly

 

 

anywhere in nearly arbitrary volume.” The limitations depend largely on how “cloudy” or cloud-aware the service/component is, and hence the need for better software architecture. (Eric A. Marks and Roberto Lozano [Executive Guide to Cloud Computing]). The reusable evolution through service architecture reinforces a focus on business objectives as opposed to the number of computing platforms to support. As a viable resource management alternative, cloud computing is fundamentally changing the way we think about computing solutions in retail, education, and public sectors. The use of cloud computing architecture and standards are driving unique ways in which computing solutions are delivered, as well as platform diversity to meet bottom-line business objectives. Thomas Erl’s body of work on service technology guided the technology industry through eloquent illustrations and literature over the past decade. Thomas’ brilliant efforts on principles, concepts, patterns, and expressions gave the information technology community an evolved software architecture approach that now forms a foundation for cloud computing goals to be successfully fulfilled in practice. This is a key assertion, as cloud computing is no longer a far-reaching concept of the future, but rather a dominant information technology service option and resource delivery presence. Thomas’ Cloud Computing: Concepts, Technology & Architecture takes the industry beyond the definitions of cloud computing and juxtaposes virtualization, grid, and sustainment strategies as contrasted in day to day operations. Thomas and his team of authors take the reader from beginning to end with the essential elements of cloud computing, its history, innovation, and demand. Through case studies and architectural models they articulate service requirements, infrastructure, security, and outsourcing of salient computing resources. Thomas again enlightens the industry with poignant analysis and reliable architecture-driven practices and principles. No matter the level of interest or experience, the reader will find clear value in this in-depth, vendor-neutral study of cloud computing. Pamela J. Wise-Martinez, Inventor and Chief Architect Department of Energy, National Nuclear Security Administration (Disclaimer: The views expressed are the personal views of the author and are not intended to reflect either the views of the U.S. Government, the U.S. Department of Energy, or the National Nuclear Security Administration.)

 

 

Acknowledgments

In alphabetical order by last name: • Ahmed Aamer, AlFaisaliah Group • Randy Adkins, Modus21 • Melanie Allison, Integrated Consulting Services • Gabriela Inacio Alves, University of Brasilia • Marcelo Ancelmo, IBM Rational Software Services • Kapil Bakshi, Cisco Systems • Toufic Boubez, Metafor Software • Antonio Bruno, UBS AG • Dr. Paul Buhler, Modus21 • Pethuru Raj Cheliah, Wipro • Kevin Davis, Ph.D. • Suzanne D’Souza, KBACE Technologies • Alexander Gromoff, Center of Information Control Technologies • Chris Haddad, WSO2 • Richard Hill, University of Derby • Michaela Iorga, Ph.D. • Johan Kumps, RealDolmen • Gijs in ’t Veld, Motion10 • Masykur Marhendra, Consulting Workforce Accenture • Damian Maschek, Deutshe Bahn • Claynor Mazzarolo, IBTI • Steve Millidge, C2B2 • Jorge Minguez, Thales Deutschland • Scott Morrison, Layer 7 • Amin Naserpour, HP • Vicente Navarro, European Space Agency • Laura Olson, IBM WebSphere • Tony Pallas, Intel

 

 

• Cesare Pautasso, University of Lugano • Sergey Popov, Liberty Global International • Olivier Poupeney, Dreamface Interactive • Alex Rankov, EMC • Dan Rosanova, West Monroe Partners • Jaime Ryan, Layer 7 • Filippos Santas, Credit Suisse • Christoph Schittko, Microsoft • Guido Schmutz, Trivadis • Mark Skilton, Capgemini • Gary Smith, CloudComputingArchitect.com • Vijay Srinivasan, Cognizant • Daniel Starcevich, Raytheon • Roger Stoffers, HP • Andre Toffanello, IBTI • Andre Tost, IBM Software Group • Bernd Trops, talend • Clemens Utschig, Boehringer Ingelheim Pharma • Ignaz Wanders, Archimiddle • Philip Wik, Redflex • Jorge Williams, Rackspace • Dr. Johannes Maria Zaha • Jeff Zhong, Futrend Technologies

Special thanks to the CloudSchool.com research and development team that produced the CCP course modules upon which this book is based.

 

 

Chapter 1. Introduction

1.1 Objectives of This Book 1.2 What This Book Does Not Cover 1.3 Who This Book Is For 1.4 How This Book Is Organized 1.5 Conventions 1.6 Additional Information

The past couple of decades saw the business-centric concept of outsourcing services and the technology-centric notion of utility computing evolve along relatively parallel streams. When they finally met to form a technology landscape with a compelling business case and seismic impacts on the IT industry as a whole, it became evident that what resultantly was termed and branded as “cloud computing” was more than just another IT trend. It had become an opportunity to further align and advance the goals of the business with the capabilities of technology.

 

 

Those who understand this opportunity can seize it to leverage proven and mature components of cloud platforms to not only fulfill existing strategic business goals, but to even inspire businesses to set new objectives and directions based on the extent to which cloud-driven innovation can further help optimize business operations. The first step to succeeding is education. Cloud computing adoption is not trivial. The cloud computing marketplace is unregulated. And, not all products and technologies branded with “cloud” are, in fact, sufficiently mature to realize or even supportive of realizing actual cloud computing benefits. To add to the confusion, there are different definitions and interpretations of cloud-based models and frameworks floating around IT literature and the IT media space, which leads to different IT professionals acquiring different types of cloud computing expertise. And then, of course, there is the fact that cloud computing is, at its essence, a form of service provisioning. As with any type of service we intend to hire or outsource (IT-related or otherwise), it is commonly understood that we will be confronted with a marketplace comprised of service providers of varying quality and reliability. Some may offer attractive rates and terms, but may have unproven business histories or highly proprietary environments. Others may have a solid business background, but may demand higher rates and less flexible terms. Others yet, may simply be insincere or temporary business ventures that unexpectedly disappear or are acquired within a short period of time. Back to the importance of getting educated. There is no greater danger to a business than approaching cloud computing adoption with ignorance. The magnitude of a failed adoption effort not only correspondingly impacts IT departments, but can actually regress a business to a point where it finds itself steps behind from where it was prior to the adoption—and, perhaps, even more steps behind competitors that have been successful at achieving their goals in the meantime. Cloud computing has much to offer but its roadmap is riddled with pitfalls, ambiguities, and mistruths. The best way to navigate this landscape is to chart each part of the journey by making educated decisions about how and to what extent your project should proceed. The scope of an adoption is equally important to its approach, and both of these aspects need to be determined by business requirements. Not by a product vendor, not by a cloud vendor, and not by self-proclaimed cloud experts. Your organization’s business goals must be fulfilled in a concrete and measurable manner with each completed phase of the adoption. This validates your scope, your approach, and the overall direction of

 

 

the project. In other words, it keeps your project aligned. Gaining a vendor-neutral understanding of cloud computing from an industry perspective empowers you with the clarity necessary to determine what is factually cloud-related and what is not, as well as what is relevant to your business requirements and what is not. With this information you can establish criteria that will allow you to filter out the parts of the cloud computing product and service provider marketplaces to focus on what has the most potential to help you and your business to succeed. We developed this book to assist you with this goal. —Thomas Erl

1.1. Objectives of This Book This book is the result of more than two years of research and analysis of the commercial cloud computing industry, cloud computing vendor platforms, and further innovation and contributions made by cloud computing industry standards organizations and practitioners. The purpose of this book is to break down proven and mature cloud computing technologies and practices into a series of well-defined concepts, models, and technology mechanisms and architectures. The resulting chapters establish concrete, academic coverage of fundamental aspects of cloud computing concepts and technologies. The range of topics covered is documented using vendor-neutral terms and descriptions, carefully defined to ensure full alignment with the cloud computing industry as a whole.

1.2. What This Book Does Not Cover Due to the vendor-neutral basis of this book, it does not contain any significant coverage of cloud computing vendor products, services, or technologies. This book is complementary to other titles that provide product-specific coverage and to vendor product literature itself. If you are new to the commercial cloud computing landscape, you are encouraged to use this book as a starting point before proceeding to books and courses that are proprietary to vendor product lines.

1.3. Who This Book Is For This book is aimed at the following target audience:

• IT practitioners and professionals who require vendor-neutral coverage of cloud computing technologies, concepts, mechanisms, and models

 

 

• IT managers and decision makers who seek clarity regarding the business and technological implications of cloud computing • professors and students and educational institutions that require well- researched and well-defined academic coverage of fundamental cloud computing topics • business managers who need to assess the potential economic gains and viability of adopting cloud computing resources • technology architects and developers who want to understand the different moving parts that comprise contemporary cloud platforms

1.4. How This Book Is Organized The book begins with Chapters 1 and 2 providing introductory content and background information for the case studies. All subsequent chapters are organized into the following parts:

• Part I: Fundamental Cloud Computing • Part II: Cloud Computing Mechanisms • Part III: Cloud Computing Architecture • Part IV: Working with Clouds • Part V: Appendices

Part I: Fundamental Cloud Computing The four chapters in this part cover introductory topics in preparation for all subsequent chapters. Note that Chapters 3 and 4 do not contain case study content. Chapter 3: Understanding Cloud Computing

Following a brief history of cloud computing and a discussion of business drivers and technology innovations, basic terminology and concepts are introduced, along with descriptions of common benefits and challenges of cloud computing adoption. Chapter 4: Fundamental Concepts and Models

Cloud delivery and cloud deployment models are discussed in detail, following sections that establish common cloud characteristics and roles and boundaries. Chapter 5: Cloud-Enabling Technology

Contemporary technologies that realize modern-day cloud computing platforms and innovations are discussed, including data centers, virtualization, and Web-

 

 

based technologies. Chapter 6: Fundamental Cloud Security

Security topics and concepts relevant and distinct to cloud computing are introduced, including descriptions of common cloud security threats and attacks.

Part II: Cloud Computing Mechanisms Technology mechanisms represent well-defined IT artifacts that are established within an IT industry and commonly distinct to a certain computing model or platform. The technology-centric nature of cloud computing requires the establishment of a formal level of mechanisms to be able to explore how solutions can be assembled via different combinations of mechanism implementations. This part formally documents 20 technology mechanisms that are used within cloud environments to enable generic and specialized forms of functionality. Each mechanism description is accompanied by a case study example that demonstrates its usage. The utilization of the mechanisms is further explored throughout the technology architectures covered in Part III. Chapter 7: Cloud Infrastructure Mechanisms

Technology mechanisms foundational to cloud platforms are covered, including Logical Network Perimeter, Virtual Server, Cloud Storage Device, Cloud Usage Monitor, Resource Replication, and Ready-Made Environment. Chapter 8: Specialized Cloud Mechanisms

A range of specialized technology mechanisms is described, including Automated Scaling Listener, Load Balancer, SLA Monitor, Pay-Per-Use Monitor, Audit Monitor, Failover System, Hypervisor, Resource Cluster, Multi- Device Broker, and State Management Database. Chapter 9: Cloud Management Mechanisms

Mechanisms that enable the hands-on administration and management of cloud- based IT resources are explained, including Remote Administration System, Resource Management System, SLA Management System, and Billing Management System. Chapter 10: Cloud Security Mechanisms

Security mechanisms that can be used to counter and prevent the threats described in Chapter 6 are covered, including Encryption, Hashing, Digital Signatures, Public Key Infrastructures (PKI), Identity and Access Management

 

 

(IAM) Systems, Single Sign-On (SSO), Cloud-Based Security Groups, and Hardened Virtual Server Images.

Part III: Cloud Computing Architecture Technology architecture within the realm of cloud computing introduces requirements and considerations that manifest themselves in broadly scoped architectural layers and numerous distinct architectural models. This set of chapters builds upon the coverage of cloud computing mechanisms from Part II by formally documenting 29 cloud-based technology architectures and scenarios in which different combinations of the mechanisms are documented in relation to fundamental, advanced, and specialized cloud architectures. Chapter 11: Fundamental Cloud Architectures

Fundamental cloud architectural models establish baseline functions and capabilities. The architectures covered in this chapter are Workload Distribution, Resource Pooling, Dynamic Scalability, Elastic Resource Capacity, Service Load Balancing, Cloud Bursting, Elastic Disk Provisioning, and Redundant Storage. Chapter 12: Advanced Cloud Architectures

Advanced cloud architectural models establish sophisticated and complex environments, several of which directly build upon fundamental models. The architectures covered in this chapter are Hypervisor Clustering, Load Balanced Virtual Server Instances, Non-Disruptive Service Relocation, Zero Downtime, Cloud Balancing, Resource Reservation, Dynamic Failure Detection and Recovery, Bare-Metal Provisioning, Rapid Provisioning, and Storage Workload Management. Chapter 13: Specialized Cloud Architectures

Specialized cloud architectural models address distinct functional areas. The architectures covered in this chapter are Direct I/O Access, Direct LUN Access, Dynamic Data Normalization, Elastic Network Capacity, Cross-Storage Device Vertical Tiering, Intra-Storage Device Vertical Data Tiering, Load-Balanced Virtual Switches, Multipath Resource Access, Persistent Virtual Network Configuration, Redundant Physical Connection for Virtual Servers, and Storage Maintenance Window. Note that this chapter does not contain a case study example.

Part IV: Working with Clouds Cloud computing technologies and environments can be adopted to varying

 

 

extents. An organization can migrate select IT resources to a cloud, while keeping all other IT resources on-premise—or it can form significant dependencies on a cloud platform by migrating larger amounts of IT resources or even using the cloud environment to create them. For any organization, it is important to assess a potential adoption from a practical and business-centric perspective in order to pinpoint the most common factors that pertain to financial investments, business impact, and various legal considerations. This set of chapters explores these and other topics related to the real-world considerations of working with cloud-based environments. Chapter 14: Cloud Delivery Model Considerations

Cloud environments need to be built and evolved by cloud providers in response to cloud consumer requirements. Cloud consumers can use clouds to create or migrate IT resources to, subsequent to their assuming administrative responsibilities. This chapter provides a technical understanding of cloud delivery models from both the provider and consumer perspectives, each of which offers revealing insights into the inner workings and architectural layers of cloud environments. Chapter 15: Cost Metrics and Pricing Models

Cost metrics for network, server, storage, and software usage are described, along with various formulas for calculating integration and ownership costs related to cloud environments. The chapter concludes with a discussion of cost management topics as they relate to common business terms used by cloud provider vendors. Chapter 16: Service Quality Metrics and SLAs

Service level agreements establish the guarantees and usage terms for cloud services and are often determined by the business terms agreed upon by cloud consumers and cloud providers. This chapter provides detailed insight into how cloud provider guarantees are expressed and structured via SLAs, along with metrics and formulas for calculating common SLA values, such as availability, reliability, performance, scalability, and resiliency.

Part V: Appendices Appendix A: Case Study Conclusions

The individual storylines of the case studies are concluded and the results of each organization’s cloud computing adoption efforts are summarized. Appendix B: Industry Standards Organizations

 

 

This appendix describes industry standards organizations and efforts in support of the cloud computing industry. Appendix C: Mapping Mechanisms to Characteristics

A table is provided, mapping cloud characteristics to the cloud computing mechanisms that can help realize the characteristics. Appendix D: Data Center Facilities (TIA-942)

A brief overview and breakdown of common data center facilities in reference to the TIA-942 Telecommunications Infrastructure Standard for Data Centers. Appendix E: Emerging Technologies

Autonomic computing and grid technology are briefly discussed as two primary technologies anticipated to influence cloud computing. Appendix F: Cloud Provisioning Contracts

The actual agreements signed between cloud provider vendors and cloud consumer organizations are distinct legal contracts that encompass a range of specific terms and considerations. This appendix highlights the typical parts of a cloud provisioning contract, and provides further guidelines. Appendix G: Cloud Business Case Template

This appendix provides a checklist of items that can be used as a starting point for assembling a business case for the adoption of cloud computing.

1.5. Conventions Symbols and Figures This book contains a series of diagrams that are referred to as figures. The primary symbols used throughout the figures are individually described in the symbol legend located on the inside of the book cover. Full-color, high- resolution versions of all figures in this book can be viewed and downloaded at www.servicetechbooks.com and www.informit.com/title/9780133387520.

Summary of Key Points For quick reference purposes, each of the sections within Chapters 3 through 6 in Part I, “Fundamental Cloud Computing,” concludes with a Summary of Key Points sub-section that concisely highlights the primary statements made within the section, in bullet list format.

1.6. Additional Information

 

 

These sections provide supplementary information and resources for the Prentice Hall Service Technology Series from Thomas Erl.

Updates, Errata, and Resources (www.servicetechbooks.com) Information about other series titles and various supporting resources can be found at the official book series Web site: www.servicetechbooks.com. You are encouraged to visit this site regularly to check for content changes and corrections.

Referenced Specifications (www.servicetechspecs.com) This site provides a central portal to the original specification documents created and maintained by primary standards organizations, with a section dedicated exclusively to cloud computing industry standards.

The Service Technology Magazine (www.servicetechmag.com) The Service Technology Magazine is a monthly publication provided by Arcitura Education Inc. and Prentice Hall and is officially associated with the Prentice Hall Service Technology Series from Thomas Erl. The Service Technology Magazine is dedicated to publishing specialized articles, case studies, and papers by industry experts and professionals.

International Service Technology Symposium (www.servicetechsymposium.com) This site is dedicated to the International Service Technology Symposium conference series. These events are held throughout the world and frequently feature authors from the Prentice Hall Service Technology Series from Thomas Erl.

What Is Cloud? (www.whatiscloud.com) A quick reference site comprised of excerpts from this book to provide coverage of fundamental cloud computing topics.

What Is REST? (www.whatisrest.com) This Web site provides a concise overview of REST architecture and constraints. REST services are referenced in Chapter 5 of this book as one of the possible implementation mediums for cloud services.

Cloud Computing Design Patterns (www.cloudpatterns.org) The cloud computing design patterns master catalog is published on this site. The mechanisms described in this book are referenced as implementation

 

 

options for various design patterns that represent established practices and technology feature-sets.

Service-Orientation (www.serviceorientation.com) This site provide papers, book excerpts, and various content dedicated to describing and defining the service-orientation paradigm, associated principles, and the service-oriented technology architectural model.

CloudSchool.com™ Certified Cloud (CCP) Professional (www.cloudschool.com) The official site for the Cloud Certified Professional (CCP) curriculum dedicated to specialized areas of cloud computing, including technology, architecture, governance, security, capacity, virtualization, and storage.

SOASchool.com® SOA Certified (SOACP) Professional (www.soaschool.com) The official site for the SOA Certified Professional (SOACP) curriculum dedicated to specialized areas of service-oriented architecture and service- orientation, including analysis, architecture, governance, security, development, and quality assurance.

Notification Service To be automatically notified of new book releases in this series, new supplementary content for this title, or key changes to the aforementioned resource sites, use the notification form at www.servicetechbooks.com or send a blank e-mail to notify@arcitura.com.

 

 
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PSEUDOCODE

Write the pseudocode using modules and show how your module will be called for the following example:

BMI is often used to determine whether a person is overweight or underweight based on height and weight. The calculation uses the following formula:

BMI = Weight x 703/Height2

Design a program that calculates and displays a person’s body mass index (BMI).

Your 3-4 page document must include:

  • Pseudo code for the entire program.
  • Internal documentation, using block and/or line comments.
  • You must declare all variables before using them in your pseudo code. Don’t forget that variables are just names. You need to assign values to variables. For example:
    Set price = 20
    Or
    Set dollars = 2.75
  • Your pseudo code must illustrate all calculations and modules called.

 

Create a flowchart showing how your module will be called for the BMI example from your Module 03 lab:

BMI is often used to determine whether a person is overweight or underweight based on height and weight. The calculation uses the following formula:

BMI = Weight x 703/Height2

Design a program that calculates and displays a person’s body mass index (BMI)

Your submission must include:

  • You may use Microsoft Visio or http://draw.io/ to create your flowchart and export the drawing as a JPG. Paste your image in your Word document with your pseudo code. Use File >> Export As >> Image.
  • Your flowchart must depict each step in the program, as well as the module.
  • Your flowchart must use 3 types of symbols: ovals (start and end terminal symbols), parallelograms (input and output symbols), and rectangles (processing symbols).
  • All symbols must be connected by arrows that represent the flow of the program. The flow must make logical sense.
 
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Basic Optimization

ISYE 6740 Homework 3

Total 100 points.

1. Basic optimization. (30 points.)

Consider a simplied logistic regression problem. Given m training samples (xi; yi), i = 1; : : : ;m.

The data xi 2 R (note that we only have one feature for each sample), and yi 2 f0; 1g. To t a

logistic regression model for classication, we solve the following optimization problem, where 2 R

is a parameter we aim to nd:

max

`(); (1)

where the log-likelhood function

`() =

Xm

i=1

f???? log(1 + expf????xig) + (yi ???? 1)xig :

(a) (10 points) Show step-by-step mathematical derivation for the gradient of the cost function `()

in (1) and write a pseudo-code for performing gradient descent to nd the optimizer . This is

essentially what the training procedure does. (pseudo-code means you will write down the steps

of the algorithm, not necessarily any specic programming language.)

(b) (10 points) Present a stochastic gradient descent algorithm to solve the training of logistic

regression problem (1).

(c) (10 points) We will show that the training problem in basic logistic regression problem

is concave. Derive the Hessian matrix of `() and based on this, show the training problem (1)

is concave (note that in this case, since we only have one feature, the Hessian matrix is just a

scalar). Explain why the problem can be solved eciently and gradient descent will achieve a

unique global optimizer, as we discussed in class.

2. Comparing Bayes, logistic, and KNN classiers. (30 points)

In lectures we learn three dierent classiers. This question is to implement and compare them. We are

suggest use Scikit-learn, which is a commonly-used and powerful Python library with various machine

learning tools. But you can also use other similar library in other languages of your choice to perform

the tasks.

Part One (Divorce classication/prediction). (20 points)

This dataset is about participants who completed the personal information form and a divorce predic-

tors scale.

The data is a modied version of the publicly available at https://archive.ics.uci.edu/ml/datasets/

Divorce+Predictors+data+set (by injecting noise so you will not replicate the results on uci web-

site). There are 170 participants and 54 attributes (or predictor variables) that are all real-valued. The

dataset marriage.csv. The last column of the CSV le is label y (1 means \divorce”, 0 means \no

divorce”). Each column is for one feature (predictor variable), and each row is a sample (participant).

A detailed explanation for each feature (predictor variable) can be found at the website link above.

Our goal is to build a classier using training data, such that given a test sample, we can classify (or

essentially predict) whether its label is 0 (\no divorce”) or 1 (\divorce”).

1

Build three classiers using (Naive Bayes, Logistic Regression, KNN). Use the rst 80% data for

training and the remaining 20% for testing. If you use scikit-learn you can use train test split to split

the dataset.

Remark: Please note that, here, for Naive Bayes, this means that we have to estimate the variance for

each individual feature from training data. When estimating the variance, if the variance is zero to

close to zero (meaning that there is very little variability in the feature), you can set the variance to

be a small number, e.g., = 10????3. We do not want to have include zero or nearly variance in Naive

Bayes. This tip holds for both Part One and Part Two of this question.

(a) (10 points) Report testing accuracy for each of the three classiers. Comment on their perfor-

mance: which performs the best and make a guess why they perform the best in this setting.

(b) (10 points) Use the rst two features to train three new classiers. Plot the data points and

decision boundary of each classier. Comment on the dierence between the decision boundary

for the three classiers. Please clearly represent the data points with dierent labels using dierent

colors.

Part Two (Handwritten digits classication). (10 points) Repeat the above using the MNIST

Data in our Homework 2. Here, give \digit” 6 label y = 1, and give \digit” 2 label y = 0. All the

pixels in each image will be the feature (predictor variables) for that sample (i.e., image). Our goal

is to build classier to such that given a new test sample, we can tell is it a 2 or a 6. Using the rst

80% of the samples for training and remaining 20% for testing. Report the classication accuracy on

testing data, for each of the three classiers. Comment on their performance: which performs the best

and make a guess why they perform the best in this setting.

3. Naive Bayes for spam ltering. (40 points)

In this problem we will use the Naive Bayes algorithm to t a spam lter by hand. This will en-

hance your understanding to Bayes classier and build intuition. This question does not involve any

programming but only derivation and hand calculation.

Spam lters are used in all email services to classify received emails as \Spam” or \Not Spam”. A

simple approach involves maintaining a vocabulary of words that commonly occur in \Spam” emails

and classifying an email as \Spam” if the number of words from the dictionary that are present in the

email is over a certain threshold. We are given the vocabulary consists of 15 words

V = fsecret, oer, low, price, valued, customer, today, dollar, million, sports, is, for, play, healthy, pizzag:

We will use Vi to represent the ith word in V . As our training dataset, we are also given 3 example

spam messages,

• million dollar oer

• secret oer today

• secret is secret

and 4 example non-spam messages

• low price for valued customer

• play secret sports today

• sports is healthy

• low price pizza

2

Recall that the Naive Bayes classier assumes the probability of an input depends on its input feature.

The feature for each sample is dened as x(i) = [x(i)

1 ; x(i)

2 ; : : : ; x(i)

d ]T , i = 1; : : : ;m and the class of the

ith sample is y(i). In our case the length of the input vector is d = 15, which is equal to the number

of words in the vocabulary V . Each entry x(i)

j is equal to the number of times word Vj occurs in the

i-th message.

(a) (5 points) Calculate class prior P(y = 0) and P(y = 1) from the training data, where y = 0

corresponds to spam messages, and y = 1 corresponds to non-spam messages. Note that these

class prior essentially corresponds to the frequency of each class in the training sample.

(b) (10 points) Write down the feature vectors for each spam and non-spam messages.

(c) (15 points) In the Naive Bayes model, assuming the keywords are independent of each other (this

is a simplication), the likelihood of a sentence with its feature vector x given a class c is given

by

P(xjy = c) =

Yd

k=1

xk

c;k; c = f0; 1g

where 0 c;k 1 is the probability of word k appearing in class c, which satises

Xd

k=1

c;k = 1; 8c:

Given this, the complete log-likelihood function for our training data is given by

`(1;1; : : : ; 1;d; 2;1; : : : ; 2;d) =

Xm

i=1

Xd

k=1

x(i)

k log y(i);k

(In this example, m = 7.) Calculate the maximum likelihood estimates of 0;1, 0;7, 1;1, 1;15 by

maximizing the log-likelihood function above. (Hint: We are solving a constrained maximization

problem. To do this, remember, you need to introduce two Lagrangian multiplier because you

have two constraints.)

(d) (10 points) Given a test message \today is secret”, using the Naive Bayes classier that you have

trained in Part (a)-(c), to calculate the posterior and decide whether it is spam or not spam.

 
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Java Homework

(Note: I have attached the book below)

(pg number 971)

24.3:  (Implement a doubly linked list) The MyLinkedList class used in Listing 24.5 is

a one-way directional linked list that enables one-way traversal of the list. Modify

the Node class to add the new data field name previous to refer to the previous

node in the list, as follows:

public class Node<E> {

E element;

Node<E> next;

Node<E> previous;

public Node(E e) {

element = e;

}

}

Implement a new class named TwoWayLinkedList that uses a doubly linked list

to store elements. Define TwoWayLinkedList to implements MyList. You need

to implement all the methods defined in MyLinkedList as well as the methods

listIterator() and listIterator(int index). Both return an instance of

java.util.ListIterator<E> (see Figure 20.4). The former sets the cursor to

the head of the list and the latter to the element at the specified index.

 
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CO SCI Simnet Project Access Ch 4 Fix It 4.6

CustomerID FirstName LastName StreetAddress City ZipCode Phone Newsletter
AG01 Antonio Gonzalez 702 Columbia Road West Palm Beach 33403 5615559361 true
AW01 Anthony Willett 1274 Valley Street West Palm Beach 33412 5615557939 false
BG01 Bruce Garber 1107 Murry Street Ft. Lauderdale 33312 9545554473 true
CF01 Caroline Fredette 4123 Five Points West Palm Beach 33403 5615550634 false
CS01 Charlotte Sager 749 Petunia Way Miami 33156 3055552879 true
DB01 Dale Brown 4849 Sunrise Road West Palm Beach 33401 5615552312 false
DD01 David Duron 1317 Everette Lane West Palm Beach 33414 5615555510 false
DT01 Danny Tweed 711 Duke Lane Miami 33183 3055557623 false
EM01 Emily McNabb 3633 Armbrester Drive Miami 33134 3055557363 false
GE01 Genevieve Eades 1941 Collins Avenue West Palm Beach 33401 5615554819 false
GP01 Gerald Price 3735 Jadewood Drive Ft. Lauderdale 33312 9545556754 false
HH01 Heidi Hartzell 2204 Plainfield Avenue Ft. Lauderdale 33301 9545553859 true
JA01 Joe Alleyne 2086 Lewis Street Miami 33176 3055553748 true
JB01 Juan Bettencourt 4769 Pinewood Avenue West Palm Beach 33412 5615554509 true
JC01 John Castellano 56 Waldeck Street Miami 33176 3055557731 false
JD01 Jeff Defelice 2202 Boone Street Miami 33134 3055559012 true
JM01 Jason Mayer 2331 Upland Avenue Miami 33183 3055551956 false
JW01 Jeffery Weldon 3775 Willow Oaks Lane Ft. Lauderdale 33305 9545556243 true
MB01 Melinda Bocanegra 355 Garrett Street Miami 33156 3055555648 true
MN01 Marvin Numbers 4630 Meadowcrest Lane Ft. Lauderdale 33305 9545554366 true
MZ01 Min Zhou 3952 Hewes Avenue Ft. Lauderdale 33316 9545554386 false
NG01 Nora Gomez 3182 Roguski Road Ft. Lauderdale 33316 9545559177 true
NW01 Nathan Westmoreland 4066 Glen Street West Palm Beach 33414 5615550096 true
PE01 Philip Elson 2905 Washington Street Miami 33186 3055551028 false
RR01 Russell Rand 3320 Sharon Lane West Palm Beach 33417 5615552958 true
RR02 Ronald Rayner 3670 Beechwood Drive West Palm Beach 33417 5615551141 true
RS01 Roberta Storm 2191 Jarvis Street Miami 33186 3055550049 true
RW01 Ralph Whitacre 590 Grant View Drive Ft. Lauderdale 33304 9545554512 true
SD01 Steve Diggs 2860 Godfrey Road Ft. Lauderdale 33304 9545551017 false
TW01 Thomas Walk 2474 Croft Drive Ft. Lauderdale 33301 9545559960 false
PetID AnimalType Breed MainColor AgeInMonths AdoptionFee Field1
144601 Cat Bengal Brown 3 ¤ 50.00
147883 Dog Fox Terrier White 5 ¤ 95.00
208636 Dog Siberian Husky Gray 3 ¤ 180.00
217716 Cat American Shorthair White 2 ¤ 20.00
236936 Dog Bull Terrier White 3 ¤ 135.00
267349 Cat Siamese Beige 4 ¤ 35.00
308359 Dog Labrador Retriever Brown 4 ¤ 120.00
366426 Dog Pomeranian Beige 3 ¤ 145.00
382848 Dog American Eskimo Dog White 5 ¤ 220.00
412745 Dog Chihuahua Brown 4 ¤ 90.00
451472 Cat Turkish Angora White 3 ¤ 95.00
453557 Dog Boxer Beige 3 ¤ 210.00
458263 Dog Poodle White 4 ¤ 75.00
466448 Cat American Shorthair Calico 2 ¤ 20.00
481238 Dog Chihuahua White 4 ¤ 75.00
495646 Dog Dachshund Brown 3 ¤ 105.00
519192 Dog Labrador Retriever Brown 4 ¤ 165.00
520691 Cat American Bobtail Brown Tabby 4 ¤ 30.00
571764 Cat Himalayan White 5 ¤ 60.00
599703 Cat American Shorthair Black 4 ¤ 20.00
661399 Cat Savannah Beige Tabby 5 ¤ 105.00
665054 Dog Irish Setter Brown 5 ¤ 175.00
678221 Cat Persian White 4 ¤ 100.00
718056 Cat Scottish Fold Gray 4 ¤ 75.00
723951 Dog Golden Retriever Beige 5 ¤ 180.00
763290 Cat American Shorthair Orange Tabby 2 ¤ 20.00
796859 Cat Manx Gray Tabby 3 ¤ 50.00
797129 Cat American Shorthair Silver Tabby 3 ¤ 20.00
831176 Dog Old English Sheepdog White 4 ¤ 175.00
858070 Cat Maine Coon Gray Tabby 3 ¤ 75.00
883940 Dog Giant Schnauzer Black 4 ¤ 110.00
909445 Dog Labrador Retriever Chocolate 4 ¤ 150.00
910387 Dog Cocker Spaniel Beige 3 ¤ 145.00
SELECT Pets.PetID, Pets.AnimalType, Pets.Breed, Pets.MainColor, Pets.AgeInMonths FROM Pets WHERE (((Pets.AgeInMonths)=0));
SELECT Customers.CustomerID, Customers.FirstName, Customers.LastName, Customers.Phone, Customers.Newsletter FROM Customers;
SELECT Customers.FirstName, Customers.LastName, Customers.StreetAddress, Customers.City, Customers.ZipCode, Customers.Phone, Customers.Newsletter FROM Customers WHERE (((Customers.LastName)=”B”)) OR (((Customers.LastName)=”W”));
SELECT Pets.AnimalType, Pets.Breed, Pets.MainColor, Pets.AgeInMonths, Pets.AdoptionFee FROM Pets WHERE (((Pets.AnimalType)=”Dog”)) OR (((Pets.AgeInMonths)=4));
SELECT Pets.AnimalType, Pets.Breed, Pets.MainColor, Pets.AgeInMonths, Pets.AdoptionFee, 1.1 AS AdoptionFee FROM Pets;
 
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Homework Assignment: Module 2 – Process Analysis 10 Questions 1. Posh Nails Katie Posh Runs

Homework Assignment: Module 2 – Process Analysis 10 questions 1. Posh Nails Katie Posh runs an upscale nail salon. The service process includes five activities that are conducted in the sequence described below. (The time required for each activity is shown in parentheses):Activity 1: Welcome a guest. (1 minute)Activity 2: Clip and file nails. (3 minutes)Activity 3: Paint. (5 minutes)Activity 4: Dry. (10 minutes)Activity 5: Check out the customer. (4 minutes)Three servers (S1, S2, and S3) offer the services in a worker-paced line. The assignment of tasks to servers is the following: S1 does Activity 1. S2 does Activities 2 and 3. S3 does Activities 4 and 5. The drying process does not require server 3’s constant attention; she/he needs to only escort the customer to the salon’s drying chair (equipped with fans for drying). The time to do this is negligible. There exists only one drying chair in the salon. Which resource is the bottleneck of the process? Dryer chair S3S2S12. Posh Nails Katie Posh runs an upscale nail salon. The service process includes five activities that are conducted in the sequence described below. (The time required for each activity is shown in parentheses): Activity 1: Welcome a guest. (1 minute)Activity 2: Clip and file nails. (3 minutes)Activity 3: Paint. (5 minutes)Activity 4: Dry. (10 minutes)Activity 5: Check out the customer. (4 minutes)Three servers (S1, S2, and S3) offer the services in a worker-paced line. The assignment of tasks to servers is the following: S1 does Activity 1. S2 does Activities 2 and 3. S3 does Activities 4 and 5. The drying process does not require server 3’s constant attention; she/he needs to only escort the customer to the salon’s drying chair (equipped with fans for drying). The time to do this is negligible. There exists only one drying chair in the salon. What is the utilization of server 2 (in decimal form)? Assume that there is unlimited demand and that the process only admits customers at the rate of the bottleneck. Enter answer here3. Posh Nails Katie Posh runs an upscale nail salon. The service process includes five activities that are conducted in the sequence described below. (The time required for each activity is shown in parentheses):Activity 1: Welcome a guest. (1 minute) Activity 2: Clip and file nails. (3 minutes)Activity 3: Paint. (5 minutes) Activity 4: Dry. (10 minutes) Activity 5: Check out the customer. (4 minutes)Three servers (S1, S2, and S3) offer the services in a worker-paced line. The assignment of tasks to servers is the following: S1 does Activity 1. S2 does Activities 2 and 3. S3 does Activities 4 and 5. The drying process does not require server 3’s constant attention; she/he needs to only escort the customer to the salon’s drying chair (equipped with fans for drying). The time to do this is negligible. There exists only one drying chair in the salon. What is the average labor utilization of the servers (in decimal form)? Assume that there is unlimited demand and that the process only admits customers at the rate of the bottleneck. Enter answer here4. Posh NailsKatie Posh runs an upscale nail salon. The service process includes five activities that are conducted in the sequence described below. (The time required for each activity is shown in parentheses):Activity 1: Welcome a guest. (1 minute) Activity 2: Clip and file nails. (3 minutes)Activity 3: Paint. (5 minutes)Activity 4: Dry. (10 minutes)Activity 5: Check out the customer. (4 minutes)Three servers (S1, S2, and S3) offer the services in a worker-paced line. The assignment of tasks to servers is the following: S1 does Activity 1. S2 does Activities 2 and 3. S3 does Activities 4 and 5. The drying process does not require server 3’s constant attention; she/he needs to only escort the customer to the salon’s drying chair (equipped with fans for drying). The time to do this is negligible. There exists only one drying chair in the salon. Assume a wage rate of $12 per hour. What are the direct labor costs for one customer (in dollars)? Enter answer here 5. BN1. Butternut is a ski resort in Massachusetts. One of their triple chair lifts unloads 1296 skiers per hour at the top of the slope. (A triple chair lift can carry three passengers per chair. Note that each lift contains multiple chairs.) The ride from the bottom to the top takes 5 minutes. On average, how many skiers are riding on the lift at any one time? Enter answer here 6. Tech Company is a medium-sized consumer electronics retailer. The company reported $155,000,000 in revenues for 2007 and $110,050,000 in Costs of Goods Sold (COGS). In the same year, Tech Co. held an average of $20,000,000 in inventory. How many times did Tech Co. turn its inventory in 2007? Enter answer here7. Tech Company is a medium-sized consumer electronics retailer. The company reported $155,000,000 in revenues for 2007 and $110,050,000 in Costs of Goods Sold (COGS). In the same year, Tech Co. held an average of $20,000,000 in inventory. Inventory cost at Tech Co. is 35 percent per year. What is the per unit inventory cost (in dollars) for an MP3 player sold at $50? Assume that the margin corresponds to the retailer’s average margin. Enter answer here8. The Gamer Company is a video game production company that specializes in educational video games for kids. The company’s R&D department is always looking for great ideas for new games. On average, the R&D department generates about 25 new ideas a week. To go from idea to approved product, the idea must pass through the following stages: paper screening (a 1-page document describing the idea and giving a rough sketch of the design), prototype development, testing, and a focus group. At the end of each stage, successful ideas enter the next stage. All other ideas are dropped. The following chart depicts this process, and the probability of succeeding at each stage. The paper screening for each idea takes 2 hours of a staff member’s time. After that, there is a stage of designing and producing a prototype. A designer spends 4 hours designing the game in a computer-aided-design (CAD) package. The actual creation of the mock-up is outsourced to one of many suppliers with essentially limitless capacity. It takes 4 days to get the prototype programmed, and multiple prototypes can be created simultaneously. A staff member of the testing team needs 2 days to test an idea. Running the focus group takes 2 hours of a staff member’s time per idea, and only one game is tested in each focus group. Finally, the management team meets for 3 hours per idea to decide if the game should go into production. Available working hours for each staff member are 8 hours per day, 5 days a week. The current staffing plan is as follows: A. Paper screening: 3 staff members. B. Design and Production: 4 staff members. C. Testing: 6 staff members. D. Focus Group: 1 staff member. E. Final Decision: 1 management team How many new ideas would Gamer Co. approve for production per week if it had unlimited capacity (staff) in its R&D process? Enter answer here 9. The Gamer Company is a video game production company that specializes in educational video games for kids. The company’s R&D department is always looking for great ideas for new games. On average, the R&D department generates about 25 new ideas a week. To go from idea to approved product, the idea must pass through the following stages: paper screening (a 1-page document describing the idea and giving a rough sketch of the design), prototype development, testing, and a focus group. At the end of each stage, successful ideas enter the next stage. All other ideas are dropped. The following chart depicts this process, and the probability of succeeding at each stage. The paper screening for each idea takes 2 hours of a staff member’s time. After that, there is a stage of designing and producing a prototype. A designer spends 4 hours designing the game in a computer-aided-design (CAD) package. The actual creation of the mock-up is outsourced to one of many suppliers with essentially limitless capacity. It takes 4 days to get the prototype programmed, and multiple prototypes can be created simultaneously. A staff member of the testing team needs 2 days to test an idea. Running the focus group takes 2 hours of a staff member’s time per idea, and only one game is tested in each focus group. Finally, the management team meets for 3 hours per idea to decide if the game should go into production. Available working hours for each staff member are 8 hours per day, 5 days a week. The current staffing plan is as follows: A. Paper screening: 3 staff members. B. Design and Production: 4 staff members. C. Testing: 6 staff members. D. Focus Group: 1 staff member. E. Final Decision: 1 management team Which stage is the bottleneck according to the current staffing plan? Testing Final decision Focus group Paper screening Design and production 10. The Gamer Company is a video game production company that specializes in educational video games for kids. The company’s R&D department is always looking for great ideas for new games. On average, the R&D department generates about 25 new ideas a week. To go from idea to approved product, the idea must pass through the following stages: paper screening (a 1-page document describing the idea and giving a rough sketch of the design), prototype development, testing, and a focus group. At the end of each stage, successful ideas enter the next stage. All other ideas are dropped. The following chart depicts this process, and the probability of succeeding at each stage. The paper screening for each idea takes 2 hours of a staff member’s time. After that, there is a stage of designing and producing a prototype. A designer spends 4 hours designing the game in a computer-aided-design (CAD) package. The actual creation of the mock-up is outsourced to one of many suppliers with essentially limitless capacity. It takes 4 days to get the prototype programmed, and multiple prototypes can be created simultaneously. A staff member of the testing team needs 2 days to test an idea. Running the focus group takes 2 hours of a staff member’s time per idea, and only one game is tested in each focus group. Finally, the management team meets for 3 hours per idea to decide if the game should go into production. Available working hours for each staff member are 8 hours per day, 5 days a week. The current staffing plan is as follows: A. Paper screening: 3 staff members. B. Design and Production: 4 staff members. C. Testing: 6 staff members. D. Focus Group: 1 staff member. E. Final Decision: 1 management team. With the current staffing plan, how many new ideas will be put into production per week?

 
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Terminal And Bash

## Week 3 Homework: A High Stakes Investigation ### Scenario You have just been hired by Lucky Duck Casino as a security analyst. – Lucky Duck has lost a significant amount of money on the roulette tables over the last month. – The largest losses occurred on March 10, 12, and 15. – Your manager believes there is a player working with a Lucky Duck dealer to steal money at the roulette tables. – The casino has a large database with data on wins and losses, player analysis, and dealer schedules. – You are tasked with navigating, modifying, and analyzing these data files to gather evidence on the rogue player and dealer. – You will prepare several evidence files to assist the prosecution. – You must work quickly as Lucky Duck can’t afford any more losses. Lucky Duck Casino has provided you with the following files if required: – [Roulette Player Data: Week of March 10](Resources/Roulette_Player_WinLoss_0310.zip) – [Employee Dealer Schedule: Week of March 10](Resources/Dealer_Schedules_0310.zip) **Note**: The instructions ask you to set up the files using a `wget` command, but the files are also provided in compressed zip format if the command does not work. ### Lab Environment – You will use your local Vagrant virtual machine for today’s activities. Please note that instructors and students have different access credentials. – Username: `sysadmin` – Password: `cybersecurity` ### Instructions Use your command-line skills to uncover the identities of the rogue casino player and dealer colluding to scam Lucky Duck out of thousands of dollars. After your investigation, you will provide a summary of your findings to the casino. #### Step 1: Investigation Preparation Your first task is to set up directories to prepare for your investigation. 1. Begin by making a single directory titled `Lucky_Duck_Investigations`. 2. In this directory, create a directory for this specific investigation titled `Roulette_Loss_Investigation`. 3. In `Roulette_Loss_Investigation`, create the following directories: – `Player_Analysis` to investigate the casino player. – `Dealer_Analysis` to investigate the dealers. – `Player_Dealer_Correlation` to summarize your findings of the collusion. 4. Create empty files called `Notes_<Directory Name>` under each subdirectory to store investigation notes. – For example: `Notes_Player_Analysis` #### Step 2: Gathering Evidence Your next task is to move evidence from the specific days that Lucky Duck experienced heavy losses at the roulette tables. 1. Navigate to the directory where you created the `Lucky_Duck_Investigations` directory and run the following command to set up the evidence files: – `wget “https://tinyurl.com/3-HW-setup-evidence” && chmod +x ./3-HW-setup-evidence && ./3-HW-setup-evidence` After running this command your current directory should have the following subdirectories: – `Dealer_Schedules_0310`: Contains the dealer schedules. – `Lucky_Duck_Investigations`: Contains the investigation directories and notes files you created. – `Roulette_Player_WinLoss_0310`: Contains the data for player wins and losses. 2. The `Dealer_Schedules_0310` and `Roulette_Player_WinLoss_0310` directories contain the dealer schedules and win/loss player data from the roulette tables during the week of March 10. – Since the losses occurred on March 10, 12, and 15, move the schedules for those days into the directory `Dealer_Analysis`. – Move the files for those days into the directory `Player_Analysis`. #### Step 3: Correlating the Evidence Your next task is to correlate the large losses from the roulette tables with the dealer schedule. This will help you determine which dealer and player are colluding to steal money from Lucky Duck. **Note:** Winnings for Lucky Duck Casino are indicated with a positive number and losses are indicated with a negative number. Complete the player analysis. 1. Navigate to the `Player_Analysis` directory. 2. Use `grep` to isolate all of the losses that occurred on March 10, 12, and 15. 3. Place those results in a file called `Roulette_Losses`. 4. Preview the file `Roulette_Losses` and analyze the data. – Record in the `Notes_Player_Analysis` file: – The times the losses occurred on each day. – If there is a certain player that was playing during each of those times. – The total count of times this player was playing. – **Hint:** Use the `wc` command to find this value. Complete the dealer analysis. 1. Navigate to the `Dealer_Analysis` directory. 2. This file contains the dealer schedules for the various Lucky Duck casino games: Blackjack, Roulette, and Texas Hold ‘Em. – Preview the schedule to view the format and to understand how the data is separated. 3. Using your findings from the player analysis, create a separate script to look at each day and time that you determined losses occurred. Use `awk`, `pipes`, and `grep` to isolate out the following four fields: – Time – a.m./p.m. – First name of roulette dealer – Last name of roulette dealer For example, if a loss occurred on March 10 at 2 p.m., you would write one script to find the roulette dealer who was working at that specific day and time. – **Hint:** You will have many scripts, but only a small change is required for each script. 5. Run all of the scripts and append those results to a file called `Dealers_working_during_losses`. 6. Preview your file `Dealers_working_during_losses` and analyze the data. – Record in the `Notes_Dealer_Analysis` file: – The primary dealer working at the times where losses occurred. – How many times the dealer worked when major losses occurred. 3. Complete the player/employee correlation. – In the notes file of the `Player_Dealer_Correlation` directory, add a summary of your findings noting the player and dealer you believe are colluding to scam Lucky Duck. – Make sure to document your specific reasons for this finding. #### Step 4: Scripting Your Tasks You manager is impressed with the work you have done so far on the investigation. They tasked you with building a shell script that can easily analyze future employee schedules. They will use this to determine which employee was working at a specific time in the case of future losses. Complete the following tasks: 1. Remain in the `Dealer_Analysis` directory. Develop a shell script called `roulette_dealer_finder_by_time.sh` that can analyze the employee schedule to easily find the roulette dealer at a specific time. **Hint:** You will be using a script similar to the one you created for the dealer analysis step, but you will not output the results into a file. – Design the shell script to accept the following two arguments: – One for the date (four digits) – One for the time **Note:** The argument should be able to accept a.m. or p.m. 3. Test your script on the schedules to confirm it outputs the correct dealer at the time specified. #### Bonus – In case there is future fraud on the other Lucky Duck games, create a shell script called `roulette_dealer_finder_by_time_and_game.sh` that has the three following arguments: – Specific time – Specific date – Casino game being played **Hint:** The argument does not need to name the specific casino game. ### Submission Guidelines – Move the following to the `Player_Dealer_Correlation` directory: – All note files – Evidence files: – `Roulette_Losses` – `Dealers_working_during_losses` – Shell script(s) – Compress the `Player_Dealer_Correlation` folder to a zip file and submit it. — © 2020 Trilogy Education Services, a 2U, Inc. brand. All Rights Reserved.

 
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Encryption And Decryption Using Vigenere With Cipher Block Chaining: Up To 50 Dollars Will Be Given

Modular Arithmetic Dr. Y. Chu CIS3360: Security in Computing 0R02 Spring 2018

1

Information

Reading: Appendix B.2 in textbook (will be posted in Webcourses)

Reference: online tutorials

2

Modulo Operation

Given any positive integer n and any integer a, when a is divided by n, we get an integer quotient, q, and integer remainder, b, that obey the following relationship:

a = q · n + b, where 0 <= b <= n-1

Then we define b= a modulo n or b= a mod n.

Note: b (modular value) is always non-negative

Examples:

5 mod 11 = 5, 5=0x11+5, so q=0 and b=5

17 mod 11 = 6, 17=1×11+6, so q=1 and b=6

-11 mod 7 = 3. (-11)=(-2)x7+3, so q=-2 and b=3

3

b is always non-negative

Congruent Modulo

Two integers, a and b, are congruent modulo n if and only if a mod n = b mod n

When a and b are divided by n, they have the same remainder

a ≡ b (mod n) ⇔ a mod n = b mod n

Example:

100 mod 11 = 1; 34 mod 11 = 1

So 100 ≡ 34 (mod 11)

In arithmetic modulo n, a and b are equivalent if their difference, (a – b), is a multiple of n

n | (a – b)

Example:

10 ≡ 2 (mod 4) because 4 | (10 − 2)

4

Modular Arithmetic

Modular arithmetic is ‘clock arithmetic’

For clock, time goes from 1 to 12, and back to 1 again

For modulo arithmetic, we start with 0, go up to n-1, and then go back to 0

Modular arithmetic uses a finite number of values, and loops back from either end

When we do modular arithmetic, we can first perform the operation and then modulo reduce the answer

Examples:

( 12 + 8 ) mod 5 = 20 mod 5 = 0

( 12 x 8 ) mod 5 = 96 mod 5 = 1

5

Modulo Reduction

The results of modular computations must remain within Zn = {0, 1, 2, … n-1}

For large values, modulo reduction is used to simplify modular computations.

Modulo properties:

Reducing each intermediate result modulo n yields the same result as doing the entire calculation, and then reducing the result to modulo n

For integers a, b, and c, and for positive n, we have:

( a + b ) mod n = ( ( a mod n ) + ( b mod n ) ) mod n

( a – b ) mod n = ( ( a mod n ) – ( b mod n ) ) mod n

( a · b ) mod n = ( ( a mod n ) · ( b mod n ) ) mod n

a (b+c) mod n = ( ( a b mod n ) · ( a c mod n ) ) mod n

Examples

( 12 + 8 ) mod 5 = ( ( 12 mod 5 ) + ( 8 mod 5 ) ) mod 5 = ( 2 + 3 ) mod 5 = 5 mod 5 = 0

(12 – 8) mod 5 = ( (12 mod 5 ) – ( 8 mod 5) ) mod 5 = ( 2 – 3 ) mod 5 = -1 mod 5 = 4

( 12 · 8 ) mod 5 = ( ( 12 mod 5 ) · ( 8 mod 5 ) ) mod 5 = ( 2 · 3 ) mod 5 = 6 mod 5 = 1

26 mod 5 = ( ( 22 mod 5 ) · ( 24 mod 5 ) ) mod 5 = (( 4 mod 5 ) · ( 16 mod 5 ) ) mod 5= (4*1) mod 5 = 4

Other properties:

Transitive law: a ≡ b ≡ c, then a ≡ c

Commutative: a + b = b + a

Associative: (a + b) + c = a + (b + c)

Distributive: a(b + c) = ab + ac

6

Modular Inverse

Given two positive integers x and y, both less than some other positive integer n, we say that y is the modular inverse of x, modulo n, and x is the modular inverse of y, modulo n,

if and only if (x · y) mod n = 1, for 0 < x < n and 0 < y < n

x-1 = y (mod n)

Example:

Prove 7 and 3 are inverses modulo 10

Steps:

Compute the multiplication

Compute the modulo value of the result

If the modulo value is 1, the numbers are inverses

7 · 3 = 21

21 mod 10 = 1

Since the modulo value is 1, 7 and 3 are inverses modulo 10

7

Properties of Modular Inverse

The number 1 is always the modular inverse of 1 for any modulus.

Not all values less than a particular modulus have inverses

Inverse of 2, mod 14 does not exist

Look at the row of 2

This row does not have 1

For the number a and modulo n, the inverse can be found if a and n are relatively prime

Relatively prime: two numbers a, n are relatively prime if gcd(a,n) = 1, where gcd is greatest common divisor

In the table, we can see 1, 3, 5, 9, 11 and 13 are relatively prime to 14.

So those rows contains 1, indicating modular inverses

8

Mod 14 multiplication table

Summary

What is Modulo Operation

Concept of Congruent Modulo

Modular Arithmetic

Modulo Reduction

Modular Inverse

Properties of Modular Inverse

9

 
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