Information Processing And Routing In Wireless Sensor Networks

By: Bhaskar Krishnamachari, Yang Yu, Viktor K Prasanna

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Hardcover | 7 December 2006

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204 Pages

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This book presents state-of-the-art cross-layer optimization techniques for energy-efficient information processing and routing in wireless sensor networks. Besides providing a survey on this important research area, three specific topics are discussed in detail - information processing in a collocated cluster, information transport over a tree substrate, and information routing for computationally intensive applications. The book covers several important system knobs for cross-layer optimization, including voltage scaling, rate adaptation, and tunable compression. By exploring tradeoffs of energy versus latency and computation versus communication using these knobs, significant energy conservation is achieved.

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Non-Fiction Engineering & Technology Electronics & Communications Engineering Communications Engineering & Telecommunications Computing & I.T.Computer Networking & Communications Technology in General Computer Hardware Network Hardware Booktopia Publisher Services World Scientific Publishing

Preface	p. vii
Introduction to Wireless Sensor Networks	p. 1
Overview	p. 1
Enabling Technologies	p. 2
Hardware	p. 2
Wireless Networking	p. 4
Collaborative Signal Processing	p. 5
Evolution of Sensor Nodes	p. 5
Military Networks of Sensors	p. 6
Next Generation Wireless Sensor Nodes	p. 6
WINS from UCLA	p. 6
Motes from UC Berkeley	p. 7
Medusa from UCLA	p. 9
PicoRadio from UC Berkeley	p. 10
[mu]AMPS from MIT	p. 11
Why Microscopic Sensor Nodes?	p. 12
Applications of Interest	p. 13
Data Gathering Applications	p. 14
Habitat Study	p. 14
Environmental Monitoring	p. 15
Computation-Intensive Applications	p. 15
Structural Health Monitoring	p. 15
Heavy Industrial Monitoring	p. 16
Research Topics and Challenges	p. 17
Focus of This Book	p. 19
Background	p. 23
Data-Centric Paradigm	p. 23
Collaborative Information Processing and Routing	p. 24
Cross-Layer Optimization for Energy-Efficiency	p. 27
Motivation	p. 27
Consideration for Collaborative Information Processing and Routing	p. 29
A Brief Survey of Cross-Layer Optimization for Energy-Efficient Collaborative Information Processing and Routing	p. 31
Hardware Layer	p. 31
Physical Layer	p. 32
MAC Layer	p. 34
Routing Layer	p. 35
Application Layer	p. 37
Summary	p. 38
Energy Models	p. 41
Definitions and Notations	p. 41
Mathematics and Graphs	p. 41
Network Topology Graph	p. 42
Application Graph	p. 43
Performance Metrics	p. 45
Energy Models	p. 47
Voltage Scaling	p. 48
Rate Adaptation	p. 49
Tunable Compression	p. 52
Information Processing within a Collocated Cluster	p. 55
Overview	p. 55
Motivation	p. 55
Technical Overview	p. 56
Chapter Organization	p. 57
Related Work	p. 57
Problem Definition	p. 58
System Model	p. 58
Application Model	p. 60
Task Allocation	p. 60
Integer Linear Programming Formulation	p. 61
Heuristic Approach	p. 63
Phase 1	p. 64
Phase 2	p. 66
Phase 3	p. 67
Simulation Results	p. 73
Synthetic Application Graphs	p. 73
Simulation Setup	p. 74
Small Scale Problems	p. 75
Large Scale Problems	p. 77
Impact of the Number of Voltage Levels	p. 79
Incorporating Rate Adaptation	p. 80
Application Graphs from Real World Problems	p. 81
LU Factorization	p. 81
Fast Fourier Transformation (FFT)	p. 83
Summary	p. 87
Information Transportation over a Tree Substrate	p. 89
Overview	p. 89
Motivation	p. 89
Technical Overview	p. 91
Chapter Organization	p. 92
Related work	p. 92
Models and Assumptions	p. 93
Data Gathering Tree	p. 94
Data Aggregation Paradigm	p. 95
Problem Definition	p. 96
Off-Line Algorithms for PTP	p. 97
A Numerical Optimization Algorithm	p. 97
Performance Analysis for a Special Case	p. 100
A Dynamic Programming-Based Approximation Algorithm	p. 103
A Distributed On-Line Protocol	p. 105
Simulation Results	p. 108
Simulation Setup	p. 108
Performance of the Off-Line Algorithms	p. 111
Performance Overview	p. 111
Impact of Radio Parameters	p. 112
Performance of the On-Line Protocol	p. 114
Performance Overview	p. 115
Impact of Network Parameters	p. 115
Adaptability to System Variations	p. 116
Summary	p. 117
Information Routing with Tunable Compression	p. 121
Overview	p. 121
Technical Overview	p. 122
Chapter Organization	p. 123
Related Work	p. 123
Models and Assumptions	p. 125
Nomenclature	p. 125
Network Model	p. 126
Flow-Based Data Gathering	p. 127
Discussion	p. 128
An Example	p. 129
Problem Definition	p. 130
Optimal Flow in a Given Tree	p. 131
Example Revisited	p. 131
Determining the Optimal Flow	p. 132
Analytical Study of SPT and MST	p. 135
Analysis for a Grid Deployment	p. 135
Tradeoffs Between SPT and MST	p. 139
Tradeoffs for Entropy Model E1	p. 140
Tradeoffs for Entropy Model E2	p. 141
SPT is optimal for Entropy Model E3	p. 142
Summary of Grid Deployment	p. 142
A Randomized O(log[superscript 2] v) Approximation	p. 142
Simulation Results	p. 145
Simulation Setup	p. 145
Results	p. 146
Main Results	p. 146
Impact of the number of source nodes R	p. 148
Impact of the communication range r	p. 148
Summary	p. 148
Conclusions	p. 153
Concluding Remarks	p. 153
Future Work	p. 155
Adaptive Fidelity Algorithms	p. 155
A Broad View of Future Research	p. 156
Mobile Sensor Nodes	p. 156
Routing Diversity	p. 157
Sleep Scheduling	p. 158
Bibliography	p. 161
Correctness of EMR-Algo	p. 175
Performance Bound of SPT and MST for TDG problem with grid deployment	p. 181
Index	p. 183
Table of Contents provided by Ingram. All Rights Reserved.

Information Processing And Routing In Wireless Sensor Networks

At a Glance

Hardcover

Shipping

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