Optimal Application Deployment in Mobile Edge Computing Environment

Mobile edge computing has emerged as a new distributed computing paradigm that overcomes the limitations of traditional cloud computing. In an edge computing environment, an app vendor can hire computing and storage resources on edge servers for deploying their applications to deliver lower-latency services to their app users. Under a budget constraint, an optimal edge application deployment strategy allows an app vendor to deploy application instances on edge servers in a specific area and provide services to the most app users in the area. In this paper, we make the first attempt to tackle this edge application deployment (EAD) problem. Specifically, we formulate the EAD problem as a constrained optimization problem and prove its NP-hardness. Then, we propose an optimal approach named EAD-opt to find the optimal solution of EAD based on integer programming, and an approximation approach named EAD-apx to find approximate solutions in large-scale EAD scenarios efficiently. We evaluate our approaches by conducting experiments on a widely used real-world data set and a synthetic data set with comparison against two baseline approaches. The experimental results demonstrate that our approaches can solve the EAD problem effectively and efficiently.