Journal ArticleDOI
Distributed compression in a dense microsensor network
TLDR
A new domain of collaborative information communication and processing through the framework on distributed source coding using syndromes, which enables highly effective and efficient compression across a sensor network without the need to establish inter-node communication, using well-studied and fast error-correcting coding algorithms.Abstract:
Distributed nature of the sensor network architecture introduces unique challenges and opportunities for collaborative networked signal processing techniques that can potentially lead to significant performance gains. Many evolving low-power sensor network scenarios need to have high spatial density to enable reliable operation in the face of component node failures as well as to facilitate high spatial localization of events of interest. This induces a high level of network data redundancy, where spatially proximal sensor readings are highly correlated. We propose a new way of removing this redundancy in a completely distributed manner, i.e., without the sensors needing to talk, to one another. Our constructive framework for this problem is dubbed DISCUS (distributed source coding using syndromes) and is inspired by fundamental concepts from information theory. We review the main ideas, provide illustrations, and give the intuition behind the theory that enables this framework.We present a new domain of collaborative information communication and processing through the framework on distributed source coding. This framework enables highly effective and efficient compression across a sensor network without the need to establish inter-node communication, using well-studied and fast error-correcting coding algorithms.read more
Citations
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Journal ArticleDOI
Distributed Video Coding
TL;DR: The recent development of practical distributed video coding schemes is reviewed, finding that the rate-distortion performance is superior to conventional intraframe coding, but there is still a gap relative to conventional motion-compensated interframe coding.
Book
Wireless Sensor Networks: Technology, Protocols, and Applications
TL;DR: This paper describes the development of Wireless Sensors Networks and its applications, and some of the applications can be found in the Commercial and Scientific Applications of Wireless Sensor Networks and Performance and Traffic Management Issues.
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Connecting the physical world with pervasive networks
TL;DR: This article addresses the challenges and opportunities of instrumenting the physical world with pervasive networks of sensor-rich, embedded computation with a taxonomy of emerging systems and outlines the enabling technological developments.
Journal ArticleDOI
Gossip Algorithms for Distributed Signal Processing
TL;DR: An overview of recent gossip algorithms work, including convergence rate results, which are related to the number of transmitted messages and thus the amount of energy consumed in the network for gossiping, and the use of gossip algorithms for canonical signal processing tasks including distributed estimation, source localization, and compression.
Journal ArticleDOI
Distributed source coding for sensor networks
TL;DR: In this article, the authors presented an intensive discussion on two distributed source coding (DSC) techniques, namely Slepian-Wolf coding and Wyner-Ziv coding, and showed that separate encoding is as efficient as joint coding for lossless compression in channel coding.
References
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Thomas M. Cover,Joy A. Thomas +1 more
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Noiseless coding of correlated information sources
David Slepian,Jack K. Wolf +1 more
TL;DR: The minimum number of bits per character R_X and R_Y needed to encode these sequences so that they can be faithfully reproduced under a variety of assumptions regarding the encoders and decoders is determined.
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Writing on dirty paper (Corresp.)
TL;DR: It is shown that the optimal transmitter adapts its signal to the state S rather than attempting to cancel it, which is also the capacity of a standard Gaussian channel with signal-to-noise power ratio P/N.
Journal ArticleDOI
Channel coding with multilevel/phase signals
TL;DR: A coding technique is described which improves error performance of synchronous data links without sacrificing data rate or requiring more bandwidth by channel coding with expanded sets of multilevel/phase signals in a manner which increases free Euclidean distance.