TY - GEN
T1 - Online ski rental for scheduling self-powered, energy harvesting small base stations
AU - Lee, Gilsoo
AU - Saad, Walid
AU - Bennis, Mehdi
AU - Mehbodniya, Abolfazl
AU - Adachi, Fumiyuki
N1 - Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2016/7/12
Y1 - 2016/7/12
N2 - The viral and dense deployment of small cell base stations (SBSs) will lie at the heart of 5G cellular networks. However, such dense networks can consume a significant amount of energy. In order to reduce the network's reliance on unsustainable energy sources, one can deploy self-powered SBSs that rely solely on energy harvesting. Due to the uncertainty of energy arrival and the finite capacity of energy storage systems, self-powered SBSs must smartly schedule their ON and OFF operation. In this paper, the problem of ON/OFF scheduling of self-powered SBSs is studied in the presence of energy harvesting uncertainty with the goal of minimizing the tradeoff between power consumption and flow-level delay. To solve this problem, a novel approach based on the ski rental framework, a powerful online optimization tool, is proposed. To find the desired solution of the ski rental problem, a randomized online algorithm is developed to enable each SBS to autonomously decide on its ON/OFF schedule, without knowing any prior information on future energy arrivals. Simulation results show that the proposed algorithm can reduce power consumption and delay over a given time period compared to a baseline that turns SBSs ON by using an energy threshold. The results show that this performance gain can reach up to 12.7% reduction of the total cost. The results also show that the proposed algorithm can eliminate up to 72.5% of the ON/OFF switching overhead compared to the baseline approach.
AB - The viral and dense deployment of small cell base stations (SBSs) will lie at the heart of 5G cellular networks. However, such dense networks can consume a significant amount of energy. In order to reduce the network's reliance on unsustainable energy sources, one can deploy self-powered SBSs that rely solely on energy harvesting. Due to the uncertainty of energy arrival and the finite capacity of energy storage systems, self-powered SBSs must smartly schedule their ON and OFF operation. In this paper, the problem of ON/OFF scheduling of self-powered SBSs is studied in the presence of energy harvesting uncertainty with the goal of minimizing the tradeoff between power consumption and flow-level delay. To solve this problem, a novel approach based on the ski rental framework, a powerful online optimization tool, is proposed. To find the desired solution of the ski rental problem, a randomized online algorithm is developed to enable each SBS to autonomously decide on its ON/OFF schedule, without knowing any prior information on future energy arrivals. Simulation results show that the proposed algorithm can reduce power consumption and delay over a given time period compared to a baseline that turns SBSs ON by using an energy threshold. The results show that this performance gain can reach up to 12.7% reduction of the total cost. The results also show that the proposed algorithm can eliminate up to 72.5% of the ON/OFF switching overhead compared to the baseline approach.
UR - http://www.scopus.com/inward/record.url?scp=84981306413&partnerID=8YFLogxK
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U2 - 10.1109/ICC.2016.7511011
DO - 10.1109/ICC.2016.7511011
M3 - Conference contribution
AN - SCOPUS:84981306413
T3 - 2016 IEEE International Conference on Communications, ICC 2016
BT - 2016 IEEE International Conference on Communications, ICC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Communications, ICC 2016
Y2 - 22 May 2016 through 27 May 2016
ER -