Mobile Edge Computing Performance Evaluation using Stochastic Petri Nets

Abstract

Mobile Edge Computing (MEC) is a network architecture that takes advantage of resources available at the edge of the network to enhance the mobile user experience by decreasing the service latency. MEC solutions need to dynamically allocate the requests as close as possible to their users to avoid high latency. However, the request allocation does not depend only on the geographical location of the servers, but also on their requirements. The task of choosing and allocating appropriate servers in a MEC environment is challenging because it involves many parameters. This paper proposes a Stochastic Petri Net (SPN) model to represent a MEC scenario and analyze its performance. The model focuses on parameters that can directly impact the service Mean Response Time (MRT) and resource utilization level. We propose case studies with numerical analyzes using real-world values to validate the proposed model. The main objective is to provide a practical guide to assist infrastructure administrators to adapt their architectures, finding a trade-off between MRT and resource utilization level.