List of Contributors.
1. Introduction.
Part I. Fundamental Properties and Limits.
2. Information-theoretic Bounds on Sensor Network Performance
(Michael Gastpar).
2.1 Introduction.
2.2 Sensor Network Models.
2.3 Digital Architectures.
2.4 The Price of Digital Architectures.
2.5 Bounds on General Architectures.
2.6 Concluding Remarks and Some Interesting Questions.
Bibliography.
3 In-Network Information Processing in Wireless Sensor
Networks (Arvind Giridhar and P. R. Kumar).
3.1 Introduction.
3.2 Communication Complexity Model.
3.3 Computing Functions Over Wireless Networks: Spatial Reuse
and Block Computation .
3.4 Wireless Networks with Noisy Communications: Reliable
Computation in a Collocated Broadcast Network.
3.5 Towards an Information Theoretic Formulation.
3.6 Conclusion.
Bibliography.
4 The Sensing Capacity of Sensor Networks (Rohit Negi,
Yaron Rachlin, and Pradeep Khosla).
4.1 Introduction.
4.2 Sensing Capacity of Sensor Networks.
4.3 Extensions to other Sensor Network Models.
4.4 Discussion and Open Problems.
Bibliography.
5. Law of Sensor Network Lifetime and Its Applications
(Yunxia Chen and Qing Zhao).
5.1 Introduction.
5.2 Law of Network Lifetime and General Design Principle.
5.3 Fundamental Performance Limit: A Stochastic Shortest Path
Framework.
5.4 Distributed Asymptotically Optimal Transmission
Scheduling.
5.5 A Brief Overview of Network Lifetime Analysis.
5.6 Conclusion.
Bibliography.
Part II. Signal Processing for Sensor Networks.
6. Detection in Sensor Networks.
6.1 Centralized Detection.
6.2 The Classical Decentralized Detection Framework.
6.3 Decentralized Detection in Wireless Sensor Networks.
6.4 Wireless Sensor Networks.
6.5 New Paradigms.
6.6 Extensions and Generalizations.
6.7 Discussion and Concluding Remarks.
Bibliography.
7. Distributed Estimation Under Bandwidth and Energy
Constraints (Alejandro Ribeiro, Ioannis D. Schizas,
Jin-Jun Xiao, Georgios B. Giannakis and Zhi-Quan
Luo).
7.1 Distributed Quantization-Estimation.
7.2 Maximum Likelihood Estimation.
7.3 Unknown noise pdf.
7.4 Estimation of Vector parameters.
7.5 Maximum a Posteriori Probability Estimation.
7.6 Dimensionality Reduction for Distributed Estimation.
7.7 Distortion-RateAnalysis.
7.8 Conclusion.
7.9 Further Reading.
Bibliography.
8. Distributed Learning in Wireless Sensor Networks
(Joel B. Predd, Sanjeev R. Kulkarni, and H. Vincent
Poor).
8.1 Introduction.
8.2 Classical Learning.
8.3 Distributed Learningin Wireless Sensor Networks.
8.4 Distributed Learningin WSNs with a Fusion Center.
8.5 Distributed Learningin Ad-hocWSNs with In-network
Processing.
8.6 Conclusion.
Bibliography.
9. Graphical Models and Fusion in Sensor Networks
(M¨ujdat C¸ etin, Lei Chen, John W. Fisher III,
Alexander T. Ihler, O. Patrick Kreidl, Randolph L. Moses, Martin J.
Wainwright, Jason L. Williams, and Alan S. Willsky).
9.1 Introduction.
9.2 Graphical Models.
9.3 From Sensor Network Fusion to Graphical Models.
9.4 Message Censoring, Approximation,and Impacton Fusion.
9.5 The Effects of Message Approximation .
9.6 Optimizing theUse of Constrained Resources in Network
Fusion.
9.7 Conclusion.
Bibliography.
Part III. Communications, Networking and Cross-Layered
Designs.
10. Randomized Cooperative Transmission in Large-Scale
Sensor Networks (Birsen Sirkeci-Mergen and Anna
Scaglione).
10.1 Introduction.
10.2 Transmit cooperation in sensor networks.
10.3 Randomized distributed cooperative schemes.
10.4 Performance of Randomized Cooperative Codes.
10.5 Analysis of Cooperative Large-scale Networks utilizing
Randomized Cooperative Codes.
10.6 Conclusion.
10.7 Appendix.
Bibliography.
11. Application Dependent Shortest Path Routing in Ad-Hoc
Sensor Networks (Saswat Misra, Lang Tong, and Anthony
Ephremides).
11.1 Introduction.
11.2 Fundamental SPR.
11.3 SPR for MobileWireless Networks.
11.4 SPRf or Ad-Hoc Sensor Networks.
11.5 Conclusion.
11.6 A Short Review of Basic Graph Theory.
Bibliography.
12. Data-Centric and CooperativeMAC Protocols for Sensor
Networks (Yao-Win Hong and Pramod K. Varshney).
12.1 Introduction.
12.2 Traditional Medium Access Control Protocols: Random Access
and Deterministic Scheduling.
12.3 Energy Efficient MAC Protocols for Sensor
Networks.
12.4 Data-Centric MAC Protocols for Sensor Networks.
12.5 Cooperative MAC Protocol for Independent Sources.
12.6 Cooperative MAC Protocol for Correlated Sensors.
12.7 DiscussionandFutureResearchDirections.
Bibliography.
13. Game Theoretic Activation and Transmission Scheduling in
Unattended Ground Sensor Networks: A Correlated Equilibrium
Approach (Vikram Krishnamurthy, Michael Maskery, and Minh Hanh
Ngo).
13.1 Introduction.
13.2 Unattended Ground Sensor Network: Capabilities and
Objectives.
13.3 Sensor Activation as the Correlated Equilibrium of a
Noncooperative Game.
13.4 Energy Efficient Transmission Scheduling in UGSN - A Markov
Decision Process Approach.
13.5 Numerical Results.
13.6 Discussion and Extensions .
13.7 Appendix.
Bibliography.
Index.
