A Low-Cost Edge Server Placement Strategy in Wireless Metropolitan Area Networks

With the emergence of computation-intensive applications such as face recognition, natural language processing, etc., the performance of mobile devices appears to be weak. Mobile cloud computing is extensively used to cover the aforementioned shortage. However, the distance between remote cloud and mobile devices might be too far to be tolerable. Cloudlet computing, fog computing, and mobile edge computing are proposed to bring the computing resources near to the mobile devices to reduce the high delay caused by the long distance. Although there exist tremendous studies focused on the offloading strategies, where and how to place edge servers to minimize the edge server providers' cost is seldom involved. In this paper, we first investigate the problem of minimizing the number of edge servers while ensuring QoS constraints such as access delay, and the Integer Linear Programming (ILP) formulation of this problem is given. Then, we transform it into the minimum dominating set problem of graph theory and propose a greedy algorithm to solve it. The simulation results demonstrate the proposed algorithm is promising.