Hassanien / Abraham / Hagras Pervasive Computing

Innovations in Intelligent Multimedia and Applications
1. Auflage 2009
ISBN: 978-1-84882-599-4
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 461 Seiten

The main objective of pervasive computing systems is to create environments where computers become invisible by being seamlessly integrated and connected into our everyday environment, where such embedded computers can then provide inf- mation and exercise intelligent control when needed, but without being obtrusive. Pervasive computing and intelligent multimedia technologies are becoming incre- ingly important to the modern way of living. However, many of their potential applications have not yet been fully realized. Intelligent multimedia allows dynamic selection, composition and presentation of the most appropriate multimedia content based on user preferences. A variety of applications of pervasive computing and - telligent multimedia are being developed for all walks of personal and business life. Pervasive computing (often synonymously called ubiquitous computing, palpable computing or ambient intelligence) is an emerging ?eld of research that brings in revolutionary paradigms for computing models in the 21st century. Pervasive c- puting is the trend towards increasingly ubiquitous connected computing devices in the environment, a trend being brought about by a convergence of advanced el- tronic – and particularly, wireless – technologies and the Internet. Recent advances in pervasive computers, networks, telecommunications and information technology, along with the proliferation of multimedia mobile devices – such as laptops, iPods, personal digital assistants (PDAs) and cellular telephones – have further stimulated the development of intelligent pervasive multimedia applications. These key te- nologiesarecreatingamultimediarevolutionthatwillhavesigni?cantimpactacross a wide spectrum of consumer, business, healthcare and governmental domains.

Autoren/Hrsg.

Hassanien, Aboul-Ella

Abraham, Ajith

Hagras, Hani

Inhaltsverzeichnis

1;Pervasive Computing
;3
1.1;Part I Intelligent Multimedia and Pervasive Systems;20
1.1.1;1 Wireless Adaptive Therapeutic TeleGaming in a Pervasive Computing Environment;21
1.1.1.1;1.1 Introduction;22
1.1.1.2;1.2 Automatic Tracking and Assessment System;24
1.1.1.2.1;1.2.1 Instrumenting Exercise Objects;26
1.1.1.2.2;1.2.2 Task Variability;27
1.1.1.2.3;1.2.3 ATA PORTAL;27
1.1.1.3;1.3 Intellect of the ATA: Gaming System;29
1.1.1.3.1;1.3.1 Targets and Distractors;30
1.1.1.3.2;1.3.2 Difficulty Level Controls;31
1.1.1.3.3;1.3.3 Information Recorded by Gaming System;31
1.1.1.4;1.4 Gaming System Adaptive Learning Methods;32
1.1.1.4.1;1.4.1 Threshold-Based Adaptive Learning;32
1.1.1.4.2;1.4.2 Ethology and the Ethogram;33
1.1.1.4.3;1.4.3 Biologically-Inspired Adaptive Learning;34
1.1.1.4.4;1.4.4 Actor-Critic Method;35
1.1.1.4.5;1.4.5 Features and Measurements;36
1.1.1.4.6;1.4.6 Approximation Spaces;37
1.1.1.4.7;1.4.7 Rough Sets;38
1.1.1.4.8;1.4.8 Average Rough Coverage;39
1.1.1.4.9;1.4.9 Approximate Space-Based Actor-Critic Method;40
1.1.1.5;1.5 Sample Results from Physiotherapy Gaming Sessions;41
1.1.1.6;1.6 Conclusion;42
1.1.1.7;References;43
1.1.2;2 Intelligent Behaviour Modelling and Control for Mobile Manipulators;47
1.1.2.1;2.1 Introduction;47
1.1.2.2;2.2 Prior Work;48
1.1.2.3;2.3 Manipulability Measure;49
1.1.2.3.1;2.3.1 Jacobian Matrix;49
1.1.2.3.2;2.3.2 Singular Value Decomposition Method;49
1.1.2.3.3;2.3.3 Manipulability Measures;50
1.1.2.3.4;2.3.4 Optimizing the Manipulability Index of Serial Manipulators Using the SVD Method;51
1.1.2.3.4.1;2.3.4.1 The Puma 560 Manipulator: A Case Study;51
1.1.2.3.5;2.3.5 Proposed Manipulability Measure Algorithm;52
1.1.2.4;2.4 Experiments;53
1.1.2.4.1;2.4.1 The Puma 560 Manipulator;53
1.1.2.4.2;2.4.2 A Six Degrees of Freedom Serial Manipulator;55
1.1.2.4.3;2.4.3 The Mitsubishi Movemaster Manipulator;56
1.1.2.4.4;2.4.4 Experimental Results;56
1.1.2.5;2.5 Mobile Manipulator;59
1.1.2.6;2.6 RISC Mobile Manipulator;59
1.1.2.7;2.7 Modelling of the RISC;60
1.1.2.7.1;2.7.1 The Position of the Robot;60
1.1.2.7.2;2.7.2 The velocity of the robot;61
1.1.2.7.3;2.7.3 Kinematic Constraints;63
1.1.2.8;2.8 Conclusions and Future Work;63
1.1.2.9;References;64
1.1.3;3 Resource-Aware Fuzzy Logic Control of Video Streaming over IP and Wireless Networks;65
1.1.3.1;3.1 Introduction;65
1.1.3.2;3.2 Related Work on Fuzzy Logic in Telecommunications;68
1.1.3.3;3.3 Fuzzy Logic Control on the Fixed Internet;70
1.1.3.3.1;3.3.1 Calculation of the Congestion Level;71
1.1.3.3.2;3.3.2 Fuzzy Logic Controller;72
1.1.3.3.3;3.3.3 Testing FLC on a Fixed Network;73
1.1.3.3.4;3.3.4 Calibration Experiments;74
1.1.3.3.5;3.3.5 Comparison with Traditional Congestion Controllers;76
1.1.3.4;3.4 Fuzzy Logic Control on the Wireless Internet;78
1.1.3.4.1;3.4.1 Bluetooth Background;80
1.1.3.4.1.1;3.4.1.1 Fuzzy Logic Control of ARQ;80
1.1.3.4.2;3.4.2 Testing FLC on a Wireless Network;83
1.1.3.4.2.1;3.4.2.1 Buffer Specification;83
1.1.3.4.2.2;3.4.2.2 Channel Specification;83
1.1.3.4.2.3;3.4.2.3 Simulations;84
1.1.3.4.2.4;3.4.2.4 Comparison with Default ARQ;85
1.1.3.5;3.5 Future Development: Type-2 Fuzzy Logic;88
1.1.3.6;3.6 Conclusion and Discussion;90
1.1.3.7;References;91
1.1.4;4 Indexing Video Summaries for Quick Video Browsing;94
1.1.4.1;4.1 Introduction;94
1.1.4.2;4.2 The Partial Access Level;96
1.1.4.2.1;4.2.1 Classical Solution for Generating Pictorial Abstract;97
1.1.4.2.2;4.2.2 Our Solution;97
1.1.4.2.2.1;4.2.2.1 News Segmentation;98
1.1.4.2.2.2;4.2.2.2 Stories Summarization;98
1.1.4.3;4.3 The Quick Access Level;103
1.1.4.3.1;4.3.1 The Indexation Part;103
1.1.4.3.1.1;4.3.1.1 Text Extraction;103
1.1.4.3.1.2;4.3.1.2 Annotation Augmentation;107
1.1.4.3.1.3;4.3.1.3 MPEG7 to Describe News Stories Summaries;107
1.1.4.3.2;4.3.2 The Querying Part;108
1.1.4.4;4.4 Experiments;109
1.1.4.4.1;4.4.1 Experimental Results of the Partial Access Level;109
1.1.4.4.2;4.4.2 Experimental Results of the Quick Access Level;109
1.1.4.5;4.5 Conclusion;109
1.1.4.6;References;112
1.1.5;5 Sensorized Garment Augmented 3D Pervasive Virtual Reality System;113
1.1.5.1;5.1 Introduction;113
1.1.5.2;5.2 System Overview;115
1.1.5.3;5.3 Sensorized Garments – Sensor Shirt Layout;116
1.1.5.3.1;5.3.1 Sensor Shirt Stability Analysis;118
1.1.5.4;5.4 Pervasive Virtual Sense of Presence;121
1.1.5.4.1;5.4.1 Virtual Reality Projection System;122
1.1.5.4.2;5.4.2 Virtual Reality Software;122
1.1.5.4.2.1;5.4.2.1 Graphics Engine Module;123
1.1.5.4.2.2;5.4.2.2 Virtual Reality Engine (A Modular Design Approach);124
1.1.5.5;5.5 Experience Summary and Results;125
1.1.5.6;5.6 Conclusion;129
1.1.5.7;References;129
1.1.6;6 Creating Innovative Solutions for Future Hotel Rooms with Intelligent Multimedia and Pervasive Computing;132
1.1.6.1;6.1 Introduction;132
1.1.6.1.1;6.1.1 Pervasive Computing;133
1.1.6.1.2;6.1.2 Hotel Rooms of the Future;133
1.1.6.1.3;6.1.3 Chapter Aim and Objectives;133
1.1.6.1.4;6.1.4 Chapter Layout;134
1.1.6.2;6.2 Creativity and Innovation;134
1.1.6.2.1;6.2.1 Creativity;134
1.1.6.2.2;6.2.2 Innovation;135
1.1.6.2.3;6.2.3 Incremental and Radical Innovations;135
1.1.6.2.4;6.2.4 Creating Innovations;136
1.1.6.2.5;6.2.5 Sustaining Innovation;138
1.1.6.3;6.3 Concept Hotels of the Future;139
1.1.6.3.1;6.3.1 Hilton's Room of the Future;139
1.1.6.3.1.1;6.3.1.1 Test Results;140
1.1.6.3.1.2;6.3.1.2 Multimedia Facilities;140
1.1.6.3.1.3;6.3.1.3 High-Tech Bathing;140
1.1.6.3.2;6.3.2 Self Check-in Systems;141
1.1.6.4;6.4 Out-of-this-World Hotels;142
1.1.6.4.1;6.4.1 Foldable Hotel Pods;142
1.1.6.4.2;6.4.2 Resort Hotels in the Stratosphere;143
1.1.6.4.3;6.4.3 Space Hotels;143
1.1.6.4.4;6.4.4 Fanciful Hotels;144
1.1.6.4.4.1;6.4.4.1 Ice Hotel, Quebec, Canada;144
1.1.6.4.4.2;6.4.4.2 L'Hotel Machet, Paris, France;144
1.1.6.4.4.3;6.4.4.3 Tinker-Toys Hotel, Wichita, Kansas;145
1.1.6.4.4.4;6.4.4.4 Hotel-O, Sydney, Australia;145
1.1.6.4.4.5;6.4.4.5 Disney's Pyramid on Ice, Cairo, Egypt;145
1.1.6.4.4.6;6.4.4.6 Invisible Hotel, Central Park, New York;145
1.1.6.4.5;6.4.5 Technology Needs of Hotel Room of the Future;145
1.1.6.5;6.5 Innovative Ideas for Hotel Rooms;146
1.1.6.5.1;6.5.1 Intelligent Systems in Future Hotels;146
1.1.6.5.1.1;6.5.1.1 Opportunities in the Future;147
1.1.6.5.1.2;6.5.1.2 Multimedia Delivery Technology;147
1.1.6.6;6.6 Conclusions;148
1.1.6.7;References;148
1.1.7;7 Mobile Virtual Environments in Pervasive Computing;150
1.1.7.1;7.1 Introduction;150
1.1.7.2;7.2 Related Work;151
1.1.7.3;7.3 Mobile Virtual Environments;153
1.1.7.3.1;7.3.1 MVE Case Study: Client-Server Remote-Rendering Application;155
1.1.7.4;7.4 Test-Bed Architecture for Mobile Virtual Environments;156
1.1.7.4.1;7.4.1 Simulation;159
1.1.7.4.2;7.4.2 Prototype;161
1.1.7.5;7.5 Modelling Decision-Making in MVEs Using Game Theory;162
1.1.7.5.1;7.5.1 Game Theory Basic Definitions;163
1.1.7.5.1.1;7.5.1.1 Game Examples;164
1.1.7.5.2;7.5.2 Client-Server Game;165
1.1.7.5.2.1;7.5.2.1 Client;165
1.1.7.5.2.2;7.5.2.2 Server;166
1.1.7.6;7.6 Conclusion and Discussion;167
1.1.7.7;References;167
1.2;Part II Ambient Intelligence and Ubiquitous Computing;170
1.2.1;8 AI Techniques in a Context-Aware Ubiquitous Environment;171
1.2.1.1;8.1 Introduction;171
1.2.1.2;8.2 Related Work;173
1.2.1.2.1;8.2.1 Context-Awareness;173
1.2.1.2.1.1;8.2.1.1 Context;173
1.2.1.2.1.2;8.2.1.2 Context-Aware Computing;173
1.2.1.2.2;8.2.2 Frameworks;174
1.2.1.2.2.1;8.2.2.1 Stick-e Notes;174
1.2.1.2.2.2;8.2.2.2 Cooltown;174
1.2.1.2.2.3;8.2.2.3 Context Toolkit;175
1.2.1.2.2.4;8.2.2.4 Sparkle;175
1.2.1.2.2.5;8.2.2.5 Hydrogen;175
1.2.1.3;8.3 The MoBe Approach;176
1.2.1.3.1;8.3.1 Motivations;176
1.2.1.3.2;8.3.2 General Architecture;176
1.2.1.3.3;8.3.3 Main Activities and Modules;178
1.2.1.3.3.1;8.3.3.1 Context Management;178
1.2.1.3.3.2;8.3.3.2 Filter and Retrieval;179
1.2.1.3.3.3;8.3.3.3 Personalization;180
1.2.1.4;8.4 Context Inference System;181
1.2.1.4.1;8.4.1 Inferring Abstract Contexts from Concrete Contexts;181
1.2.1.4.2;8.4.2 Two Approaches for the Inferential System;181
1.2.1.4.2.1;8.4.2.1 Rule-Based Systems;181
1.2.1.4.2.2;8.4.2.2 Bayesian Networks;182
1.2.1.4.2.3;8.4.2.3 Considerations;183
1.2.1.4.3;8.4.3 The Inferential Infrastructure;183
1.2.1.4.4;8.4.4 Critical Issues;183
1.2.1.5;8.5 Context-Aware Browser;186
1.2.1.6;8.6 Usage Scenarios;187
1.2.1.6.1;8.6.1 Implementation;187
1.2.1.6.2;8.6.2 Domotics and Automotive Scenario;188
1.2.1.6.3;8.6.3 Pervasive Multimedia Social Guide;190
1.2.1.7;8.7 Conclusions and Future Work;192
1.2.1.8;References;193
1.2.2;9 A Distributed Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care;195
1.2.2.1;9.1 Introduction;195
1.2.2.2;9.2 Problem Description;197
1.2.2.3;9.3 Related Work;198
1.2.2.4;9.4 ALZ-MAS;199
1.2.2.4.1;9.4.1 Using FUSION@ to Distribute Resources;201
1.2.2.4.2;9.4.2 Technologies for Context-Awareness;204
1.2.2.5;9.5 Results and Conclusions;207
1.2.2.6;References;211
1.2.3;10 Volcano Monitoring: A Case Study in PervasiveComputing;214
1.2.3.1;10.1 Introduction;214
1.2.3.2;10.2 Literature Review;216
1.2.3.3;10.3 Ground Component;217
1.2.3.3.1;10.3.1 Power Management;218
1.2.3.3.2;10.3.2 Bandwidth Management;219
1.2.3.3.3;10.3.3 QoS Management;220
1.2.3.3.3.1;10.3.3.1 Situation Awareness;220
1.2.3.3.3.2;10.3.3.2 Prioritization;221
1.2.3.3.3.3;10.3.3.3 Link Layer Prioritization;222
1.2.3.3.3.4;10.3.3.4 Robustness;223
1.2.3.3.4;10.3.4 Topology and Routing Management;224
1.2.3.3.4.1;10.3.4.1 Sensor to Sink Routing;226
1.2.3.3.4.2;10.3.4.2 Reliable Broadcasting;229
1.2.3.3.4.3;10.3.4.3 Pipelined Sending and Receiving Between Layers for Optimization;231
1.2.3.3.5;10.3.5 Sensor Node Development;233
1.2.3.3.6;10.3.6 Smart Sensing;233
1.2.3.3.6.1;10.3.6.1 Sensing Module Challenges;233
1.2.3.4;10.4 Space Component;239
1.2.3.4.1;10.4.1 Science Products;241
1.2.3.5;10.5 Conclusion and Discussion;242
1.2.3.6;References;242
1.2.4;11 SiC: An Agent Based Architecture for Preventing and Detecting Attacks to Ubiquitous Databases;244
1.2.4.1;11.1 Introduction;244
1.2.4.2;11.2 Database Threat and Security Revision;247
1.2.4.3;11.3 An Architecture Based on Multiagent System;251
1.2.4.3.1;11.3.1 Communication Among Agents;253
1.2.4.4;11.4 Classifier Model of SQL Injection Attacks;256
1.2.4.4.1;11.4.1 Neural Network Learning Algorithm;258
1.2.4.5;11.5 Experimental Results and Discussion;264
1.2.4.6;11.6 Conclusions;268
1.2.4.7;References;269
1.2.5;12 HoCaMA: Home Care Hybrid Multiagent Architecture;272
1.2.5.1;12.1 Introduction;272
1.2.5.2;12.2 General Description of the Problem;274
1.2.5.2.1;12.2.1 The Pervasive Services in Home Care;275
1.2.5.2.2;12.2.2 Multiagent Architecture: State-of-the-Art;277
1.2.5.3;12.3 HoCaMA Architecture;279
1.2.5.3.1;12.3.1 Applications;279
1.2.5.3.2;12.3.2 Agents Platform in HoCaMA;280
1.2.5.3.2.1;12.3.2.1 CoAp Agent;281
1.2.5.3.2.2;12.3.2.2 CoSe Agent;281
1.2.5.3.2.3;12.3.2.3 Directory Agent;282
1.2.5.3.2.4;12.3.2.4 Supervisor Agent;282
1.2.5.3.2.5;12.3.2.5 Security Agent;282
1.2.5.3.2.6;12.3.2.6 Manager Agent;283
1.2.5.3.2.7;12.3.2.7 Interface Agent;283
1.2.5.3.3;12.3.3 Services;283
1.2.5.3.4;12.3.4 HoCaMA Communication Protocol;284
1.2.5.3.5;12.3.5 Location and Identification System in HoCaMA;285
1.2.5.3.5.1;12.3.5.1 Identification System, Features and Operation;285
1.2.5.3.6;12.3.6 Alert System in HoCaMA;287
1.2.5.3.6.1;12.3.6.1 Alert System Features;288
1.2.5.4;12.4 Using HoCaMA to Develop a MultiAgent System for a Home Care Environment;290
1.2.5.5;12.5 Results;295
1.2.5.6;12.6 Conclusions;296
1.2.5.7;References;297
1.3;Part III Web Service and Situation Awareness in Pervasive Computing;299
1.3.1;13 Semantic Annotation for Web Service Processes in Pervasive Computing;300
1.3.1.1;13.1 Introduction;300
1.3.1.2;13.2 Overview of the Approach: The Methodology;302
1.3.1.3;13.3 Annotation Technique;306
1.3.1.3.1;13.3.1 Datatype Annotation;307
1.3.1.3.2;13.3.2 Declarations;308
1.3.1.3.3;13.3.3 Global Assertions;308
1.3.1.3.4;13.3.4 Procedural Annotation;309
1.3.1.3.5;13.3.5 Assertions;309
1.3.1.4;13.4 Model Translation;312
1.3.1.5;13.5 Grounding and Model Checking;316
1.3.1.6;13.6 Conclusions and Discussion;320
1.3.1.7;References;321
1.3.2;14 Situation-Aware Adaptive Processing (SAAP) of Data Streams;323
1.3.2.1;14.1 Introduction;323
1.3.2.2;14.2 Situation-Aware Adaptive Processing (SAAP) of Data Streams;325
1.3.2.3;14.3 Fuzzy Situation Inference (FSI);325
1.3.2.3.1;14.3.1 The Context Spaces (CS) Model;326
1.3.2.3.2;14.3.2 Situation Modelling;327
1.3.2.3.2.1;14.3.2.1 Fuzzifier;327
1.3.2.3.2.2;14.3.2.2 Rules;328
1.3.2.3.3;14.3.3 Situation Reasoning;329
1.3.2.3.3.1;14.3.3.1 Weights and Contribution Level;330
1.3.2.3.3.2;14.3.3.2 Sensors' Inaccuracy;331
1.3.2.3.3.3;14.3.3.3 Symmetric and Asymmetric Attributes;332
1.3.2.3.3.4;14.3.3.4 Partial and Symmetric and Asymmetric Attributes;333
1.3.2.4;14.4 Adaptation Engine (AE);334
1.3.2.4.1;14.4.1 Resource-Aware Strategy;337
1.3.2.4.2;14.4.2 Situation-Aware Strategy;337
1.3.2.4.3;14.4.3 Integrated Strategy;339
1.3.2.5;14.5 Evaluation;340
1.3.2.5.1;14.5.1 FSI Evaluation;340
1.3.2.5.2;14.5.2 Evaluation of Situation-aware Adaptation;345
1.3.2.6;14.6 Conclusion;347
1.3.2.7;References;347
1.4;Part IV Pervasive Networks and E-commerce;349
1.4.1;15 A Scalable P2P Video Streaming Framework;350
1.4.1.1;15.1 Introduction;350
1.4.1.2;15.2 Centralized and Decentralized Video Streaming;352
1.4.1.2.1;15.2.1 Client/Server Streaming;353
1.4.1.2.2;15.2.2 Centralized P2P Streaming;354
1.4.1.2.3;15.2.3 Decentralized P2P Streaming;356
1.4.1.3;15.3 Multi-Description Video Coding;358
1.4.1.4;15.4 Video Frame Loss Analysis;361
1.4.1.4.1;15.4.1 Packet Loss Analysis in Client-Server Streaming;362
1.4.1.4.2;15.4.2 Packet Loss Analysis in Centralized P2P Streaming;363
1.4.1.4.3;15.4.3 Packet Loss Analysis in Decentralized P2P Streaming;365
1.4.1.4.4;15.4.4 Single Path Transmission vs. Multi-Path Transmission;366
1.4.1.5;15.5 Analysis;367
1.4.1.6;15.6 Conclusions;371
1.4.1.7;References;371
1.4.2;16 QoE in Pervasive Telecommunication Systems;373
1.4.2.1;16.1 Introduction;373
1.4.2.2;16.2 QoE Requirements for Pervasive Services;374
1.4.2.2.1;16.2.1 Mobility;374
1.4.2.2.2;16.2.2 Cost;375
1.4.2.2.3;16.2.3 Display Characteristics;375
1.4.2.2.4;16.2.4 Integration of Services;376
1.4.2.2.5;16.2.5 Usability Issues;376
1.4.2.2.6;16.2.6 Security and Privacy;377
1.4.2.2.7;16.2.7 Quality of Service Assurance;377
1.4.2.3;16.3 Case Study on QoE in a Pervasive Service;378
1.4.2.3.1;16.3.1 P2P Television Systems;378
1.4.2.3.2;16.3.2 Factors Affecting QoE for P2P Television;379
1.4.2.3.3;16.3.3 QoE Analysis of a Peer-to-Peer Television System;380
1.4.2.3.4;16.3.4 Experimental Methods;380
1.4.2.3.4.1;16.3.4.1 Measurement Methodology;381
1.4.2.3.4.2;16.3.4.2 Subjective Assessment Methodology;383
1.4.2.3.5;16.3.5 Results;384
1.4.2.3.5.1;16.3.5.1 Results from the Experimental Measurements;384
1.4.2.3.5.2;16.3.5.2 Results from the Subjective Assessment;386
1.4.2.4;16.4 Discussion;388
1.4.2.5;16.5 Conclusions;388
1.4.2.6;References;389
1.4.3;17 Agents Based e-Commerce and Securing Exchanged Information;391
1.4.3.1;17.1 Introduction;391
1.4.3.2;17.2 Background;393
1.4.3.3;17.3 Literature Review;395
1.4.3.4;17.4 Robust Security Techniques;397
1.4.3.5;17.5 Protocol Analysis;401
1.4.3.5.1;17.5.1 Protocol Formal Verification;402
1.4.3.5.2;17.5.2 Security Reasoning;406
1.4.3.5.3;17.5.3 Protocol Efficiency;408
1.4.3.6;17.6 Conclusions;409
1.4.3.7;References;410
1.4.4;18 Neighbor Selection in Peer-to-Peer Overlay Networks: A Swarm Intelligence Approach;413
1.4.4.1;18.1 Introduction;413
1.4.4.2;18.2 Related Research Work;415
1.4.4.3;18.3 NS Problem;420
1.4.4.3.1;18.3.1 Modeling P2P Networks;420
1.4.4.3.2;18.3.2 Metrics;420
1.4.4.4;18.4 Particle Swarm Heuristic for NS;422
1.4.4.4.1;18.4.1 Algorithm Design;422
1.4.4.4.2;18.4.2 Dynamic Ergodic Characteristics;427
1.4.4.4.3;18.4.3 Convergence Analysis of Multi-Swarm Algorithm;429
1.4.4.5;18.5 Algorithm Performance Demonstration;432
1.4.4.6;18.6 Conclusion;436
1.4.4.7;References;437
1.4.5;19 Analysis of Pervasive Mobile Ad Hoc Routing Protocols;440
1.4.5.1;19.1 Introduction;440
1.4.5.2;19.2 Taxonomy of Mobile Ad Hoc Routing Protocols;442
1.4.5.2.1;19.2.1 Approaches Based on Route Construction, Maintenance and Update Mechanisms;442
1.4.5.2.1.1;19.2.1.1 Proactive (Table-Driven) Routing;442
1.4.5.2.1.2;19.2.1.2 Reactive (On-Demand) Routing;442
1.4.5.2.1.3;19.2.1.3 Hybrid Routing;444
1.4.5.2.2;19.2.2 Approaches Based on Logical Organization, Network Configuration, and Utilization of Specific Resources;444
1.4.5.2.2.1;19.2.2.1 Uniform Routing;444
1.4.5.2.2.2;19.2.2.2 NonUniform Routing;445
1.4.5.3;19.3 An Overview of the Most Common Ad Hoc Routing Protocols;446
1.4.5.3.1;19.3.1 Destination Sequence Distance Vector (DSDV);446
1.4.5.3.2;19.3.2 Wireless Routing Protocol (WRP);446
1.4.5.3.3;19.3.3 Source Tree Adaptive Routing (STAR);447
1.4.5.3.4;19.3.4 Distance Routing Effect Algorithm for Mobility (DREAM);447
1.4.5.3.5;19.3.5 Fisheye State Routing (FSR);448
1.4.5.3.6;19.3.6 Ad Hoc On-Demand Distance Vector (AODV);448
1.4.5.3.7;19.3.7 Dynamic Source Routing (DSR);449
1.4.5.3.8;19.3.8 Temporally Ordered Routing Algorithm (TORA);449
1.4.5.3.9;19.3.9 Associativity-Based Routing ;450
1.4.5.3.10;19.3.10 Location Aided Routing ;450
1.4.5.3.11;19.3.11 Cluster-Based Routing Protocol (CBRP);451
1.4.5.4;19.4 Mobile Ad Hoc Routing Protocol Requirements and Performance Evaluation Metrics;451
1.4.5.4.1;19.4.1 Characteristics of Ad Hoc Routing Protocols;452
1.4.5.4.2;19.4.2 Performance Evaluation Metrics;453
1.4.5.5;19.5 Performance Analysis Based on Existing Literature;453
1.4.5.5.1;19.5.1 Approaches Based on Varying Pause Time and Traffic Load;454
1.4.5.5.2;19.5.2 Approaches Based on Varying Mobility and/or Traffic Flow;455
1.4.5.5.3;19.5.3 Approaches Based on Varying Number of Nodes;456
1.4.5.6;19.6 Discussion;457
1.4.5.7;19.7 Conclusion;458
1.4.5.8;Abbreviations;458
1.4.5.9;References;458
1.5;Index;461