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 to maximize bandwidth utilization, which is one of the most important concerns of network operators. In particular, we formulate the stochastic optimization problem as an infinite horizon average cost Markov Decision Process (MDP). 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. 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 of polynomial complexity with the numbers of users and files as well as the cache size, by a linear approximation of the value function and optimization relaxation techniques. We also propose an online decentralized algorithm to implement the proposed low-complexity decentralized policy 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.
REF designs the optimal joint pushing and caching policy to maximize the bandwidth utilization and smooth the traffic load.
Joint Pushing and Caching for Bandwidth Utilization Maximization in Wireless Networks
GLOBECOM 2017 - 2017 IEEE Global Communications Conference
GLOBECOM 2017 - 2017 IEEE Global Communications Conference
Computer Science Mathematics