Microservice Pre-Deployment Based on Mobility Prediction and Service Composition in Edge

As an emerging computing paradigm, mobile edge computing (MEC) is receiving growing attention. In MEC, user requests on software applications are firstly sent to edge servers for processing, which can significantly reduce the latency compared with sending to cloud centers. Furthermore, a software application adopting the popular microservice architecture usually contains multiple intercommunicating microservices. This suggests that the software used by a moving user will invoke different microservices on different locations. However, a microservice request may fail as no corresponding microservice is deployed on nearby edge servers due to resource limitation and coverage limitation. Moreover, if the user is moving at high speed, the user may leave the coverage of the edge server before receiving a response. To address this issue, we propose a microservice pre-deployment approach by integrating mobility prediction and service composition. Our work aims to improve the success rate of both request and response for multi-users while reducing the resource cost of pre-deployment. Three groups of experiments demonstrate that our approach can significantly improve the performance of microservice pre-deployment compared with several baseline approaches.