Proactive Caching for Energy-Efficiency in Wireless Networks: A Markov Decision Process Approach
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Abstract (arXiv)
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 textitgeneralized 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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 29 Nov 2017.
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