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Joo, Changhee
Learning, Modeling, and Networking
Research Interests
  • Learning, modeling, networking, resource allocation, stochastic optimization, distributed computing, low complexity

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A Simple Asymptotically Optimal Joint Energy Allocation and Routing Scheme in Rechargeable Sensor Networks

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Title
A Simple Asymptotically Optimal Joint Energy Allocation and Routing Scheme in Rechargeable Sensor Networks
Author
Sinha, PrasunShroff, Ness BChen, ShengboJoo, Changhee
Issue Date
2014-08
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE-ACM TRANSACTIONS ON NETWORKING, v.22, no.4, pp.1325 - 1336
Abstract
In this paper, we investigate the utility maximization problem for a sensor network with energy replenishment. Each sensor node consumes energy in its battery to generate and deliver data to its destination via multihop communications. Although the battery can be replenished from renewable energy sources, the energy allocation should be carefully designed in order to maximize system performance, especially when the replenishment profile is unknown in advance. In this paper, we address the joint problem of energy allocation and routing to maximize the total system utility, without prior knowledge of the replenishment profile. We first characterize optimal throughput of a single node under general replenishment profile and extend our idea to the multihop network case. After characterizing the optimal network utility with an upper bound, we develop a low-complexity online solution that achieves asymptotic optimality. Focusing on long-term system performance, we can greatly simplify computational complexity while maintaining high performance. We also show that our solution can be approximated by a distributed algorithm using standard optimization techniques. In addition, we show that the required battery size O(in(1/xi))is to constrain the performance of our scheme within xi-neighborhood of the optimum. Through simulations with replenishment profile traces for solar and wind energy, we numerically evaluate our solution, which outperforms a state-of-the-art scheme that is developed based on the Lyapunov optimization technique.
URI
https://scholarworks.unist.ac.kr/handle/201301/6410
URL
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84907599613
DOI
10.1109/TNET.2013.2273830
ISSN
1063-6692
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