A Novel Mobile Edge Network Architecture with Joint Caching-Delivering and Horizontal Cooperation

Mobile edge caching/computing (MEC) has been emerging as a promising paradigm to provide ultra-high rate, ultra-reliable, and/or low-latency communications in future wireless networks. In this paper, we introduce a novel MEC network architecture that leverages the optimal joint caching-delivering with horizontal cooperation among mobile edge nodes (MENs). To that end, we first formulate the content-access delay minimization problemby jointly optimizing the content caching and delivering decisions under various network constraints (e.g., network topology, storage capacity and users' demands at each MEN). However, the strongly mutual dependency between the decisions makes the problema nested dual optimization that is proved to be NP-hard. To deal with it, we propose a novel transformation method to transform the nested dual problemto an equivalent mixed-integer nonlinear programming (MINLP) optimization problem. Then, we design a centralized solution using an improved branch-and-bound algorithm with the interior-point method to find the joint caching and delivering policy which is within 1 percent of the optimal solution. Since the centralized solution requires the full network topology and information from all MENs, to make our solution scalable, we develop a distributed algorithm which allows each MEN to make its own decisions based on its local observations. Extensive simulations demonstrate that the proposed solutions can reduce the total average delay for the whole network up to 40 percent compared with other current caching policies. Furthermore, the proposed solutions also increase the cache hit ratio for the network up to 4 times, thereby dramatically reducing the traffic load on the backhaul network.

Automated summary

This paper introduces a novel MEC network architecture that leverages horizontal cooperation among MENs, enabling optimal joint caching and delivering. The authors propose a transformation method to convert the NP-hard nested dual optimization problem into a MINLP problem, and design centralized and distributed algorithms for finding solutions. Extensive simulations show that the proposed solutions can significantly reduce network delay and traffic load while increasing cache hit ratio.