SEGUE: Quality of Service Aware Edge Cloud Service Migration

摘要

Edge cloud computing moves cloud services to the edge of the network, thereby allowing clients to access services with a significantly reduced network delay. This service migration is intended to enable a range of latency sensitive mobile applications. In this paper, we propose to manage user QoS by actively migrating services to different edge clouds in response to degraded server or network performance. Previous studies have proposed a distance-based Markov Decision Process (MDP) for optimizing migration decisions. These models provide the feasibility of applying MDP to edge cloud service migration decisions. However, these models fail to consider dynamic network and server states in migration decisions. In this work, we address these limitations by designing a comprehensive edge cloud migration decision system, which we call SEGUE. SEGUE achieves optimal migration decisions by providing a long-term optimal QoS to mobile users in the presence of link quality and server load variation. The basis of SEGUE is in its QoS-aware service migration and its state based MDP model which effectively incorporates the two dominant factors in making migration decisions: 1) network state, and 2) server state. An evaluation of SEGUE performance is given through an augmented reality application. Our results demonstrate that SEGUE reduces the response time of this application by 27.21% and 53.70% compared to the lowest load migration model and the least hop migration model, respectively.