Edge server placement in mobile edge computing

• Published in: Journal of parallel and distributed computing Vol. 127; pp. 160 - 168
• Main Authors: Wang, Shangguang, Zhao, Yali, Xu, Jinlinag, Yuan, Jie, Hsu, Ching-Hsien
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.05.2019
• Subjects: Access delay; Mobile edge computing; Smart city edge server placement; Workload balancing; Workload balancing; Smart city edge server placement; Access delay; Mobile edge computing
• ISSN: 0743-7315; 1096-0848
• DOI: 10.1016/j.jpdc.2018.06.008

With the rapid increase in the development of the Internet of Things and 5G networks in the smart city context, a large amount of data (i.e., big data) is expected to be generated, resulting in increased latency for the traditional cloud computing paradigm. To reduce the latency, mobile edge computing has been considered for offloading a part of the workload from mobile devices to nearby edge servers that have sufficient computation resources. Although there has been significant research in the field of mobile edge computing, little attention has been given to understanding the placement of edge servers in smart cities to optimize the mobile edge computing network performance. In this paper, we study the edge server placement problem in mobile edge computing environments for smart cities. First, we formulate the problem as a multi-objective constraint optimization problem that places edge servers in some strategic locations with the objective to make balance the workloads of edge servers and minimize the access delay between the mobile user and edge server. Then, we adopt mixed integer programming to find the optimal solution. Experimental results based on Shanghai Telecom’s base station dataset show that our approach outperforms several representative approaches in terms of access delay and workload balancing. •Edge server placement is formulated as a multi-objective constraint optimization problem.•Access delay between mobile user and edge server is minimized.•Balance of edge servers workloads is guaranteed.•Experimental results based on Shanghai Telecom’s base station dataset verified effectiveness of the proposed techniques.