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Distributed rate control, routing, and energy management in dynamic rechargeable sensor networks

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Abstract

This paper studies the network utility maximization (NUM) problem in dynamic-routing rechargeable sensor networks (RSNs), where rate control, routing, and energy management need to be jointly optimized. This problem is very challenging since the flow constraint is spatially coupled and the energy constraint is spatiotemporally coupled (energy causality). Existing works either do not fully consider the two coupled constraints together, or heuristically remove the temporally-coupled part, both of which are not practical, and may degrade network performance. In this paper, we attempt to jointly optimize rate control, routing, and energy management by carefully tackling the flow and energy constraints. To this end, we first decouple the original problem equivalently into separable subproblems by means of dual decomposition. Then, we propose a distributed algorithm, which can converge to the globally optimal solution. Numerical results based on real solar data are presented to evaluate the optimality and scalability of the proposed algorithm.

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Notes

  1. The sink is the terminal of the entire network, and thus there is no need to consider the flow constraint on it.

  2. Obviously, \(f_{ii}^{h} = 0\), therefore, we do not separate \(f_{ii}^{h}\) out of \(\sum \nolimits _{j \in \mathcal {N}} {f_{ji}^{h}}\) or \(\sum \nolimits _{j \in \mathcal {N} \cup \{s\}} {f_{ij}^{h}}\).

  3. The sink is assumed to connect to the mains, and thus there is no need to consider the energy constraint on it.

  4. The following figures are based on the solar data of December 12, 2012. We focus on the daytime since the energy harvesting rate is zero at night.

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Acknowledgments

This work was supported in part by Alberta Innovates Technology Futures (AITF) postdoctoral fellowship, a research grant from the Natural Science and Engineering Research Council (NSERC) of Canada, a visiting scholarship of State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, China (No. 2007DA10512716407), and the Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China (No. ICT1600168).

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada, T6G 1H9

    Ruilong Deng & Hao Liang

  2. State Key Laboratory of Power Transmission Equipment, System Security and New Technology, Chongqing University, Chongqing, 400044, China

    Jing Yong

  3. Global Energy Interconnection Research Institute, State Grid Corporation of China, Beijing, 102209, China

    Bo Chai

  4. Navigation College, Dalian Maritime University, Dalian, Liaoning, 116026, China

    Tingting Yang

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  1. Ruilong Deng
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Correspondence to Hao Liang.

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Deng, R., Liang, H., Yong, J. et al. Distributed rate control, routing, and energy management in dynamic rechargeable sensor networks. Peer-to-Peer Netw. Appl. 10, 425–439 (2017). https://doi.org/10.1007/s12083-016-0515-7

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