Joint Pushing and Caching for Bandwidth Utilization Maximization in Wireless Networks

Abstract

Joint pushing and caching is recognized as an efficient remedy to the problem of spectrum scarcity incurred by tremendous mobile data traffic. In this paper, by exploiting storage resources at end users and predictability of user demand processes, we design the optimal joint pushing and caching policy to maximize bandwidth utilization, which is of fundamental importance to mobile telecom carriers.In particular, we formulate the stochastic optimization problem as an infinite horizon average cost Markov Decision Process (MDP), for which there generally exist only numerical solutions without many insights. By structural analysis, we show how the optimal policy achieves a balance between the current transmission cost and the future average transmission cost. In addition, we show that the optimal average transmission cost decreases with the cache size, revealing a tradeoff between the cache size and the bandwidth utilization. Then, due to the fact that obtaining a numerical optimal solution suffers the curse of dimensionality and implementing it requires a centralized controller and global system information, we develop a decentralized policy with polynomial complexity w.r.t. the numbers of users and files as well as cache size, by a linear approximation of the value function and optimization relaxation techniques. Next, we propose an online decentralized algorithm to implement the proposed low-complexity decentralized policy using the technique of Q-learning, when priori knowledge of user demand processes is not available. Finally, using numerical results, we demonstrate the advantage of the proposed solutions over some existing designs. The results in this paper offer useful guidelines for designing practical cache-enabled content-centric wireless networks.

Bandwidth Gain From Mobile Edge Computing and Caching in Wireless Multicast Systems

“…For example, the core idea of [10] is how to design the cache placement and coded delivery scheme to achieve global caching gain and minimize the peak transmission rate. [11] designs the optimal joint pushing and caching policy to maximize the bandwidth utilization and smooth the traffic load. [12] studies the fundamental tradeoff between storage and latency in a general wireless interference network with caches equipped at all the transmitters and receivers.…”

MDP-Based Scheduling Design for Mobile-Edge Computing Systems with Random User Arrival

“…Remark 1. In most of the existing literature on wireless resource allocation with approximate MDP [12], [13], [14], the performance can hardly be bounded analytically. The novel solution framework proposed in this paper provides a low-complexity policy whose performance can be bounded analytically.…”