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E-raamat: Mobile Applications Development with Android: Technologies and Algorithms

(Pace University, New York City, New York, USA), (Pace University, New York City, New York, USA), (Pace University, New York City, New York, USA)
  • Formaat: PDF+DRM
  • Ilmumisaeg: 14-Oct-2016
  • Kirjastus: Chapman & Hall/CRC
  • Keel: eng
  • ISBN-13: 9781498761871
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Mobile Applications Development with Android: Technologies and AlgorithmsSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 14-Oct-2016
  • Kirjastus: Chapman & Hall/CRC
  • Keel: eng
  • ISBN-13: 9781498761871
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Mobile Applications Development with Android: Technologies and Algorithms presents advanced techniques for mobile app development, and addresses recent developments in mobile technologies and wireless networks. The book covers advanced algorithms, embedded systems, novel mobile app architecture, and mobile cloud computing paradigms.

Divided into three sections, the book explores three major dimensions in the current mobile app development domain. The first section describes mobile app design and development skills, including a quick start on using Java to run an Android application on a real phone. It also introduces 2D graphics and UI design, as well as multimedia in Android mobile apps.

The second part of the book delves into advanced mobile app optimization, including an overview of mobile embedded systems and architecture. Data storage in Android, mobile optimization by dynamic programming, and mobile optimization by loop scheduling are also covered. The last section of the book looks at emerging technologies, including mobile cloud computing, advanced techniques using Big Data, and mobile Big Data storage.

About the Authors

Meikang Qiu is an Associate Professor of Computer Science at Pace University, and an adjunct professor at Columbia University. He is an IEEE/ACM Senior Member, as well as Chair of the IEEE STC (Special Technical Community) on Smart Computing. He is an Associate Editor of a dozen of journals including IEEE Transactions on Computers and IEEE Transactions on Cloud Computing. He has published 320+ peer-reviewed journal/conference papers and won 10+ Best Paper Awards.

Wenyun Dai is pursuing his PhD at Pace University. His research interests include high performance computing, mobile data privacy, resource management optimization, cloud computing, and mobile networking. His paper about mobile app privacy has been published in IEEE Transactions on Computers.

Keke Gai is pursuing his PhD at Pace University. He has published over 60 peer-reviewed journal or conference papers, and has received three IEEE Best Paper Awards. His research interests include cloud computing, cyber security, combinatorial optimization, business process modeling, enterprise architecture, and Internet computing.

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List of Figures
xiii
List of Tables
xxi
Preface xxiii
Acknowledgments xxv
Author Biographies xxvii
Section I Mobile App Design and Development Skills
Chapter 1 Overview of Mobile App and Mobile Interface
3(20)
1.1 Mobile System
4(2)
1.2 Mobile Interface and Applications
6(3)
1.2.1 Optimizations in Mobile Systems
8(1)
1.2.2 Mobile Embedded System
8(1)
1.3 Mobile Cloud
9(12)
1.3.1 Big Data Application in Mobile Systems
10(1)
1.3.2 Data Security and Privacy Protection in Mobile Systems
11(2)
1.3.3 Concept of Mobile Apps
13(1)
1.3.4 Brief Introduction of Android and Its Framework
14(1)
1.3.4.1 A Brief History of Android
14(2)
1.3.4.2 Android Device Distribution
16(1)
1.3.4.3 Android SDK
16(5)
1.4 Exercises
21(2)
Chapter 2 Quick Start on Android
23(14)
2.1 Installing Java
23(1)
2.2 Installing Integrate Development Environment
24(1)
2.3 Installing Android Sdk
25(1)
2.4 Creating An Android Application
26(1)
2.5 Android Virtual Device
27(8)
2.6 Exercises
35(2)
Chapter 3 Introduction of Key Concepts of Android
37(12)
3.1 APP Components
38(3)
3.1.1 Activities
38(1)
3.1.2 Services
38(1)
3.1.3 Content Providers
39(1)
3.1.4 Intents
39(2)
3.2 APP Resources
41(1)
3.3 APP Mainfest
42(4)
3.3.1 Elements
43(1)
3.3.2 Attributes
44(1)
3.3.3 Declaring Class Names
44(1)
3.3.4 Multiple Values
44(1)
3.3.5 Resource Values
45(1)
3.3.6 Sting Values
45(1)
3.4 Exercises
46(3)
3.4.1 Basic Exercises
46(1)
3.4.2 Advanced Exercises
47(2)
Chapter 4 2-D Graphics and Multimedia in Android
49(28)
4.1 Introduction of 2-D Graphics Techniques
50(9)
4.1.1 Color
50(2)
4.1.2 Paint
52(1)
4.1.3 Path
52(1)
4.1.4 Canvas
53(1)
4.1.5 Drawable
54(4)
4.1.6 Button Selector
58(1)
4.2 Advanced UI Design
59(5)
4.2.1 Multiple Screens
59(3)
4.2.2 Action Bar
62(1)
4.2.3 Custom Views
63(1)
4.3 Overview of Multimedia in Android
64(2)
4.3.1 Understanding the MediaPlayer Class
64(1)
4.3.2 Life Cycle of the MediaPlayer State
65(1)
4.4 Audio Implementations in Android
66(1)
4.5 Executing Video in Android
67(5)
4.6 Exercises
72(5)
4.6.1 Basic Exercises
72(2)
4.6.2 Advanced Exercises
74(3)
Section II Advanced Mobile App Optimizations
Chapter 5 Mobile Embedded System Architecture
77(32)
5.1 Embedded Systems
78(3)
5.1.1 Embedded Systems Overview
78(3)
5.2 Scheduling Algorithms
81(15)
5.2.1 Basic Concepts
81(1)
5.2.2 First-Come, First-Served Scheduling Algorithm
82(2)
5.2.3 Shorted-Job-First Scheduling Algorithm
84(1)
5.2.4 Multiprocessors
85(3)
5.2.5 Priority Scheduling Algorithm
88(3)
5.2.6 ASAP and ALAP Scheduling Algorithm
91(2)
5.2.6.1 ASAP
93(1)
5.2.6.2 ALAP
94(2)
5.3 Memory Technology
96(1)
5.4 Mobile Embedded Systems
97(5)
5.4.1 Embedded Systems in Mobile Devices
97(1)
5.4.2 Embedded Systems in Android
98(2)
5.4.3 Power Management of Android
100(1)
5.4.4 Embedded Systems in Mobile Apps
101(1)
5.5 Messaging and Communication Mechanisms
102(4)
5.5.1 Message Mechanisms
103(1)
5.5.2 Communication Mechanisms
104(2)
5.6 Exercises
106(3)
Chapter 6 Data Storage and SQLite Operations
109(22)
6.1 Local Data
110(8)
6.1.1 Internal and External Storage
110(1)
6.1.2 Save a File on Internal Storage
111(2)
6.1.3 Save a File on External Storage
113(3)
6.1.4 Delete a File
116(1)
6.1.5 Query the Space
117(1)
6.2 Sqlite Database
118(8)
6.2.1 Table Structure
119(1)
6.2.2 CRUD Operations
119(5)
6.2.3 Usage of SQLite Techniques
124(2)
6.3 Content Provider
126(2)
6.4 Exercises
128(3)
6.4.1 Basic Exercises
128(1)
6.4.2 Advanced Exercises
129(2)
Chapter 7 Mobile Optimization by Dynamic Programming
131(36)
7.1 Introduction Of Heterogeneous Embedded Systems and Dynamic Programming
133(1)
7.2 Fixed Time Model
134(9)
7.2.1 Heterogeneous Assignment
134(2)
7.2.2 Minimizing Costs by Scheduling
136(7)
7.3 Probabilistic Time Model
143(18)
7.3.1 Introduction of Probabilistic Time Model
143(4)
7.3.2 Solutions to Heterogeneous Assignment Problems
147(1)
7.3.3 Generating a D Table
147(2)
7.3.4 Example of Generating a D Table
149(12)
7.4 Nondeterministic Polynomial-Time Problems
161(1)
7.4.1 Cook's Theorem
161(1)
7.5 Exercises
162(3)
7.5.1 Fundamental Questions
162(1)
7.5.2 Practical Questions
163(2)
7.6 Glossary
165(2)
Chapter 8 Mobile Optimizations by Loop Scheduling
167(28)
8.1 Introduction
168(1)
8.2 Basic Graph Models and Techniques
169(4)
8.2.1 Data-Flow Graph in Loop Scheduling
169(2)
8.2.2 Retiming and Unfolding
171(2)
8.3 Fundamental Timing Optimizations
173(4)
8.4 Time and Power Optimizations with Loop Scheduling
177(9)
8.4.1 Probabilistic Data-Flow Graph
177(3)
8.4.2 Loop Scheduling and Parallel Computing
180(6)
8.5 Conclusions
186(1)
8.6 Exercises
187(3)
8.6.1 Fundamental Questions
187(1)
8.6.2 Practical Questions
188(2)
8.7 Glossary
190(5)
Section III Mobile App Techniques in Emerging Technologies
Chapter 9 Mobile Cloud Computing in Mobile Applications Deployment
195(26)
9.1 Introduction
196(1)
9.2 Concepts of Mobile Cloud Computing
197(11)
9.2.1 Technological Structure of Mobile Cloud Computing
197(1)
9.2.2 Differences between Cloud Computing and Mobile Cloud
198(2)
9.2.3 Mobile Computing
200(1)
9.2.4 Wireless Networks
201(1)
9.2.4.1 Wireless Local Area Networks (WLANs)
202(3)
9.2.4.2 Comparison between Wireless Local Area Networks and Wireless Fidelity
205(1)
9.2.4.3 Wireless Wide Area Network
205(1)
9.2.4.4 Cellular Network
206(2)
9.3 Main Techniques of Mobile Cloud Computing
208(4)
9.3.1 Virtualization
208(2)
9.3.2 Parallel Programming Model
210(1)
9.3.3 Mass Distributed Storage
211(1)
9.4 Mobile Cloud Computing Architecture
212(2)
9.5 Exercises
214(1)
9.5.1 Fundamental Questions
214(1)
9.5.2 Practical Questions
215(1)
9.6 Glossary
215(6)
Chapter 10 Efficient Data Synchronization on Mobile Devices in Big Data
221(34)
10.1 Overview of Big Data
222(3)
10.1.1 Understanding Data Type
222(1)
10.1.2 Categorizing Big Data Models
223(1)
10.1.3 Current Challenges in Big Data
224(1)
10.2 Big Data Processing
225(8)
10.2.1 Machine Learning
227(1)
10.2.1.1 Supervised Learning
227(4)
10.2.1.2 Unsupervised Learning
231(2)
10.2.1.3 Semisupervised Learning
233(1)
10.3 Mobile Big Data Storage
233(13)
10.3.1 Introduction and Basic Concepts
233(2)
10.3.2 Heterogeneous Memory Architecture
235(2)
10.3.3 Multi-dimensional Dynamic Programming Data Allocation
237(9)
10.4 Security and Privacy Issues
246(4)
10.5 Data Deduplication
250(1)
10.6 Exercises
251(4)
10.6.1 Fundamental Questions
251(1)
10.6.2 Practical Questions
252(3)
Section IV Appendices
Appendix 1 Project 1
255(2)
Project Description
255(1)
Project Objective
255(1)
Project Gudelines
255(1)
Project Plan
256(1)
Appendix 2 Project 2
257(4)
Project Description
257(1)
Project Objective
257(1)
Project Requirements
257(1)
Project Plan
257(4)
Appendix 3 BirthProvider.java. Codes
261(8)
Birthprovider.Java. Codes
261(8)
Bibliography 269
Meikang Qiu is an Associate Professor of Computer Science at Pace University, and an adjunct professor at Columbia University. He is an IEEE/ACM Senior Member, as well as Chair of the IEEE STC (Special Technical Community) on Smart Computing. He is an Associate Editor of a dozen of journals including IEEE Transactions on Computers and IEEE Transactions on Cloud Computing. He has published 320+ peer-reviewed journal/conference papers and won 10+ Best Paper Awards.









Wenyun Dai is pursuing his PhD at Pace University. His research interests include high performance computing, mobile data privacy, resource management optimization, cloud computing, and mobile networking. His paper about mobile app privacy has been published in IEEE Transactions on Computers.









Keke Gai is pursuing his PhD at Pace University. He has published over 60 peer-reviewed journal or conference papers, and has received three IEEE Best Paper Awards. His research interests include cloud computing, cyber security, combinatorial optimization, business process modeling, enterprise architecture, and Internet computing.
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