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research-article

Control of wireless networks with rechargeable batteries

Published: 01 February 2010 Publication History

Abstract

We consider the problem of cross-layer resource allocation for wireless networks operating with rechargeable batteries under general arrival, channel state and recharge processes. The objective is to maximize total system utility, defined as a function of the long-term rate achieved per link, while satisfying energy and power constraints. A policy with decoupled admission control and power allocation decisions is proposed that achieves asymptotic optimality for sufficiently large battery capacity to maximum transmission power ratio (explicit bounds are provided). We present first a downlink resource allocation scenario; the analysis is then extended to multihop networks. The policy is evaluated via simulations and is seen to perform very well even in the non-asymptotic regime. This policy is particularly suitable for sensor networks, which typically satisfy the asymptotic conditions required by our methodology.

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    Information & Contributors

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    Published In

    cover image IEEE Transactions on Wireless Communications
    IEEE Transactions on Wireless Communications  Volume 9, Issue 2
    February 2010
    383 pages

    Publisher

    IEEE Press

    Publication History

    Published: 01 February 2010
    Accepted: 19 October 2009
    Revised: 11 February 2009
    Received: 11 July 2008

    Author Tags

    1. Lyapunov drift
    2. Stochastic optimal control
    3. rechargeable batteries
    4. sensor networks
    5. sensor networks.
    6. stochastic optimal control

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    • (2024)Efficient Throughput Maximization in Dynamic Rechargeable NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2023.325600723:3(2254-2268)Online publication date: 1-Mar-2024
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    • (2020)Bregman-style Online Convex Optimization with EnergyHarvesting ConstraintsProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/34283374:3(1-25)Online publication date: 30-Nov-2020
    • (2020)Sharing Energy for Optimal Edge PerformanceSOFSEM 2020: Theory and Practice of Computer Science10.1007/978-3-030-38919-2_3(24-36)Online publication date: 20-Jan-2020
    • (2019)Learning-Aided Optimization for Energy-Harvesting Devices With Outdated State InformationIEEE/ACM Transactions on Networking10.1109/TNET.2019.292640327:4(1501-1514)Online publication date: 1-Aug-2019
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    • (2018)Distributed Power Control for Multi-Hop Energy Harvesting Links With RetransmissionIEEE Transactions on Wireless Communications10.1109/TWC.2018.281968517:6(4064-4078)Online publication date: 1-Jun-2018
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