Cache Placement in Fog-RANs: From Centralized to Distributed Algorithms

TL;DR

This paper explores cache placement strategies in Fog-RANs, developing centralized and distributed algorithms that optimize content caching to reduce user download delays in next-generation wireless networks.

Contribution

It introduces novel centralized and distributed cache placement algorithms tailored for Fog-RANs, considering flexible physical-layer schemes and user preferences.

Findings

Proposed algorithms significantly reduce average download delay.

Centralized algorithm achieves near-optimal solutions via matroid constrained submodular maximization.

Distributed belief propagation algorithm provides effective suboptimal solutions with local information.

Abstract

To deal with the rapid growth of high-speed and/or ultra-low latency data traffic for massive mobile users, fog radio access networks (Fog-RANs) have emerged as a promising architecture for next-generation wireless networks. In Fog-RANs, the edge nodes and user terminals possess storage, computation and communication functionalities to various degrees, which provides high flexibility for network operation, i.e., from fully centralized to fully distributed operation. In this paper, we study the cache placement problem in Fog-RANs, by taking into account flexible physical-layer transmission schemes and diverse content preferences of different users. We develop both centralized and distributed transmission aware cache placement strategies to minimize users' average download delay subject to the storage capacity constraints. In the centralized mode, the cache placement problem is transformed into a matroid constrained submodular maximization problem, and an approximation algorithm is proposed to find a solution within a constant factor to the optimum. In the distributed mode, a belief propagation based distributed algorithm is proposed to provide a suboptimal solution, with iterative updates at each BS based on locally collected information. Simulation results show that by exploiting caching and cooperation gains, the proposed transmission aware caching algorithms can greatly reduce the users' average download delay.