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Clustering-Based Algorithm for Services Deployment in Mobile Edge Computing Environment

In the edge computing, the service is deployed to the edge server through virtualization technology. Most strategies of service deployment are singleness and ignore the diversity of users' requirements and the service deployment cost at the edge. This paper proposes a clustering-based algorithm for service deployment, which considers the delay at the user side and the edge-side services deployment cost, and establishes a service deployment model based on multi-objective integer linear programming. Firstly, the K-means clustering algorithm is optimized to solve the problem of hotspot migration in the process of service deployment and reduce the deployment cost at the edge server side, then alternative enhanced heuristic algorithm is proposed to find the approximate optimal solution of services deployment. Experiments show that the algorithm can reasonably deploy services. Compared with traditional heuristic algorithms, the algorithm proposed in this paper has better performance in terms of user side and edge server side.