Ada-Things: An adaptive virtual machine monitoring and migration strategy for internet of things applications

Abstract Internet of Things (IoT) applications running on mobile devices are subject to the low storage capacity and short battery lifetime. Edge clouds (EC) provide an approach to offload computation tasks and reduce network latency for these applications. The main challenge in such ecosystems is how to efficiently monitor and allocate VM resources to realize load balancing among edge clouds. In this paper, we propose Ada-Things, an adaptive VM monitoring and live migration Strategy for IoT applications in edge cloud architecture. The basic idea of Ada-Things is that the migration method of a VM should be determined by its workload characteristics. Specifically, based on the variation of current memory dirty page rate in IoT applications, Ada-Things can adaptively select the most appropriate migration method to copy memory pages, thus addressing the two limitations (application generality and performance imbalance) of existing VM migration methods in edge cloud. Evaluation results show, compared with traditional methods, Ada-Things can significantly reduce the total migration time by 21%, the VM downtime by 38% and the amount of pages transferred by 29% in average.