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Time-expanded Method Improving Throughput in Dynamic Renewable Networks
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DOI：10.1109/IWQOS52092.2021.9521323.png)
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Abstract
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In the Dynamic Rechargeable Networks (DRNs), the existing studies usually consider the spatio-temporal dynamics of the harvested energy so as to maximize the throughput by efficient energy allocation. However, the network dynamics have seldom been considered simultaneously including the time variable link quality, communication power and battery charge efficiency. Furthermore, the wireless interference brings extra challenge. To take these dynamics into account together, this paper studies the quite challenging problem, the network throughput maximization in the DRNs, by proper energy allocation while considering the additional affection of wireless interference. We introduce the Time-Expanded Graph (TEG) to describe the above dynamics in a feasible easy way, and then look into the scenario where there is only one pair of source-target firstly. To maximize the throughput, this paper designs the Single Pair Throughput maximization (SPT) algorithm based on TEG while considering the wireless interference. In the case of multiple pairs of sourcetargets, it's quite complex to solve the network throughput maximization problem directly. This paper introduces the Garg and Konemanns framework and then designs the Multiple Pairs Throughput (MPT) algorithm to maximize the overall throughput of all pairs. MPT is a fast approximation solution with the ratio of 1-3 epsilon, where 0 < epsilon < 1 is a small positive constant. This paper also conducts the extensive numerical evaluation based on the simulated data and the data collected by our real system. The numerical simulation results demonstrate the throughput improvement of our algorithms.
Keywords:
Energy-Harvesting System
Dynamic Renewable Networks
Time-Expanded Graph
Throughput Maximization
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