Proceedings Article10.1109/CISS.2006.286455
Randomized Sequential Algorithms for Data Aggregation in Sensor Networks
Onur Savas,Murat Alanyali,Venkatesh Saligrama +2 more
- 22 Mar 2006
- pp 165-170
TL;DR: The per-node message and time complexities of the algorithms in explicit graphs as a function of the network size are studied and trade-offs between the number of messages transmitted and the computation times are suggested.
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Abstract: We consider distributed algorithms for data aggregation in sensor networks. The algorithms are admitted via message passing hence through pairwise computations. Under these algorithms a transmitting node becomes inactive until it is reactivated, yielding to substantial energy gains. We study the per-node message and time complexities of the algorithms in explicit graphs as a function of the network size. The obtained complexities are compared to those of so-called gossip algorithms. The results suggest trade-offs between the number of messages transmitted and the computation times.
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Citations
Adversarial Reasoning: Computational Approaches to Reading the Opponent's Mind
Alexander Kott,William M. McEneaney +1 more
- 01 Jul 2006
TL;DR: The notion of a syntactic interface of systems and system components, by which communication lines, which the authors call channels, the system or a system component is connected to the environment and which messages are communicated over the channels is introduced.
134
Location-Aided Fast Distributed Consensus in Wireless Networks
TL;DR: The idea of Markov chain lifting is studied to accelerate the convergence of distributed consensus, and two general pseudoalgorithms are presented that achieve the same scaling law in averaging time as the centralized scheme in wireless networks for all r satisfying the connectivity requirement.
37
Network Coding for Distributed Storage in Wireless Networks
Alexandros G. Dimakis,Kannan Ramchandran +1 more
- 01 Dec 2008
TL;DR: This work will address some of the problems related to storing information in multiple storage devices that are individually unreliable, and connected in a network, and new issues arise that have not been addressed in classical coding theory.
32
Location-Aided Fast Distributed Consensus in Wireless Networks
TL;DR: In this article, the idea of Markov chain lifting is studied to accelerate the convergence of distributed consensus, and two general pseudo-algorithms are presented, which are instantiated through a class of location-aided distributed averaging algorithms for wireless networks, where nodes' coarse location information is used to construct nonreversible chains that facilitate distributed computing and cooperative processing.
30
•Posted Content
On sensing capacity of sensor networks for the class of linear observation, fixed SNR models
TL;DR: This paper derives lower bounds to sensing capacity via deriving upper bounds to the probability of error via adaptation to a max-likelihood detection set-up under a given distortion criteria and shows the effect of correlation in sensing across sensors and across sensing modalities on sensing capacity.
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References
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