NDLI: Time and energy complexity of distributed computation in wireless sensor networks

Content Provider	IEEE Xplore Digital Library
Author	Khude, N. Kumar, A. Karnik, A.
Copyright Year	2005
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Indian Inst. of Sci., Bangalore, India (Khude, N.; Kumar, A.)
Abstract	We consider a scenario where a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing the maximum value of the measurements and communicating it to an operator station. We view the problem as one of message passing distributed computation over a geometric random graph. The network is assumed to be synchronous; at each sampling instant each sensor measures a value, and then the sensors collaboratively compute and deliver the maximum of these values to the operator station. Computation algorithms differ in the messages they need to exchange, and our formulation focuses on the problem of scheduling of the message exchanges. We do not exploit techniques such as source compression, or block coding of the computations. For this problem, we study the computation time and energy expenditure for one time maximum computation, and also the pipeline throughput. We show that, for an optimal algorithm, the computation time, energy expenditure and the achievable rate of computation scale as /spl Theta/(/spl radic/ n/log n), /spl Theta/(n) and /spl Theta/(1/log n) asymptotically (in probability) as the number of sensors n/spl rarr//spl infin/. We also analyze the performance of three specific computational algorithms, namely, the tree algorithm, multihop transmission, and the ripple algorithm, and obtain scaling laws for the computation time and energy expenditure as n/spl rarr//spl infin/. Simulation results are provided to show that our analysis indeed captures the correct scaling; the simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized scheduler and hence our results can be viewed as providing bounds for the performance with a distributed scheduler.
Starting Page	2625
Ending Page	2637
File Size	2665136
Page Count	13
File Format	PDF
ISBN	0780389689
ISSN	0743166X
DOI	10.1109/INFCOM.2005.1498546
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-03-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer networks Distributed computing Wireless sensor networks Processor scheduling Performance analysis Computational modeling Analytical models Message passing Sampling methods Collaboration
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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