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arXiv · 1711.10710

Proactive Caching for Energy-Efficiency in Wireless Networks: A Markov Decision Process Approach

Zhijie Chen·Hoshyar Mohammed·Wei Chen
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Abstract

Content caching in wireless networks provides a substantial opportunity to trade off low cost memory storage with energy consumption, yet finding the optimal causal policy with low computational complexity remains a challenge. This paper models the Joint Pushing and Caching (JPC) problem as a Markov Decision Process (MDP) and provides a solution to determine the optimal randomized policy. A novel approach to decouple the influence from buffer occupancy and user requests is proposed to turn the high-dimensional optimization problem into three low-dimensional ones. Furthermore, a non-iterative algorithm to solve one of the sub-problems is presented, exploiting a structural property we found as \textit{generalized monotonicity}, and hence significantly reduces the computational complexity. The result attains close performance in comparison with theoretical bounds from non-practical policies, while benefiting from higher time efficiency than the unadapted MDP solution.

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Zhijie Chen, Hoshyar Mohammed, Wei Chen. 2017-11-29. Proactive Caching for Energy-Efficiency in Wireless Networks: A Markov Decision Process Approach. https://doi.org/10.1109/icc.2018.8422143

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