Abstract
Edge computing is a promising alternative to cloud computing for offloading computationally heavy tasks from resource-constrained mobile user devices. Placed at the edge of the network, edge computing is particularly advantageous to delay-limited applications for having a short distance to end-users. However, when a mobile user moves away from the service coverage of the associated edge server, the advantage gradually vanishes, increasing response time. Although service migration has been studied to address this problem focusing on minimizing the service downtime, both zero-downtime and the amount of traffic generated as a result of migration need further study. In this paper, an optimal live migration for containerized edge computing service is studied. This paper presents three zero-downtime migration techniques based on state duplication and state reproduction techniques, and then, proposes an optimal migration technique selection algorithm that jointly minimizes the response time and network traffic during migration. For validation and performance comparison, the proposed migration techniques are implemented on off-the-shelf hardware with Linux operating system. The evaluation results showed that compared with a naive migration, the optimal approach reduced the response time and network load by at least 74.75% and 94.79%, respectively, under considered scenarios.
Highlights
W E are living in an era where Internet of Things (IoT) devices in the vicinity of users continuously produce massive data [1] and process them [2] to enable user-centric applications to be running on smart handheld devices
To capture the last-minute state changes, i.e., the state changes that are not included in what has been transmitted to the target edge server, this paper has proposed a packet relay and buffer replay method
This paper has proposed a system design for an autonomous optimal migration selection system. It chooses the optimal migration technique considering the characteristics of the application to be migrated and the migration methods together
Summary
W E are living in an era where Internet of Things (IoT) devices in the vicinity of users continuously produce massive data [1] and process them [2] to enable user-centric applications to be running on smart handheld devices. A user can offload its computationally-heavy tasks to its dedicated virtual machine or container running on either cloud or edge computing. This paper proposes a low-cost optimal migration selection algorithm for for it to run in real-time. The. Access Point Edge Server Mobile User Quality of Service Round Trip Time Edge Server (or Edge computing Server) ES from which the running container is migrated ES to which the running container on ES(src) is migrated Proposed Differential-Copy migration technique Proposed Full-Copy migration technique Proposed Log-Replay migration technique empirical evaluation results are presented and discussed, and the paper is concluded by Section VII.
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