Practical Enhancement and Evaluation of a Low-Latency Network Model Using Mobile Edge Computing

Abstract

Most of latency-sensitive mobile applications require computational resources provided through a cloud computing service. The problem of relying on cloud computing is that, sometimes, the physical locations of cloud servers are distant from mobile users and the communication latency is long. As a result, the concept of distributed cloud service, called mobile edge computing (MEC), is being introduced in the 5G network. However, MEC can reduce only the communication latency. The computing latency in MEC must also be considered to satisfy the required total latency of services. In this research, we study the impact of both latencies in MEC architecture with regard to latency-sensitive services. We also consider a centralized model, in which we use a controller to manage flows between users and mobile edge resources to analyze MEC in a practical architecture. The simulation results show that the controller interval and hop delay lead some blocking and error in the system. However the permissive system which relaxes latency constrains and chooses an edge server by the lowest total latency can improve the system performance impressively.