Hardware-assisted Service Live Migration in Resource-limited Edge Computing Systems

Abstract

Service live migration means migrating the running services from one machine to another with negligible service downtime. It has been considered as a powerful mechanism to facilitate service management. However, conventional live migration methods always come with expensive cost of data transmission, and thus can hardly be applied to a real-world edge computing system directly due to the limited network bandwidth. To tackle this problem, some recent works present various techniques to reduce the data transmission.However, these techniques for data transmission reduction always introduce extra computational costs, which have a great impact on the quality of service (QoS), especially in edge systems containing lots of nodes with insufficient computational resources. To alleviate this issue, we propose an insight to offload data reduction computations to a specific hardware accelerator, thus reducing the burden of CPU cores. To this end, we present a novel hardware accelerator design to speed up the data transmission reduction computations to accelerate the service live migration. For evaluation, we implement a prototype on an FPGA platform. Compared to the normal CPU-based approaches, our specialized accelerator is 3.1× faster, 2.9× more-energy efficient, and can reduce 29%∼47% of total migrating time and 24%∼40% of service downtime in our cases. Furthermore, our architecture has great scalability and is easy-configurable to achieve a balance between cost and performance.