Task Offloading and Resources Allocation based on Fairness in Edge Computing
Kaile Xiao, Zhipeng Gao, Congcong Yao, Qian Wang, Zijia Mo, Yang Yang · 2019
Task offloading has been a hot topic in the field of edge computing. Resources fairness of edge computing servers which is the destination of task offloading directly impacts life of server and the process quality of task. In this paper, we propose a subtask-virtual machine mapping model (subtask-VM mapping model) to complete task offloading from the terminals to the servers. Considering the reasonable allocation of server resources, we also propose stack-based cache mechanism (SCM) to ensure the fairness of server resources allocation. We transform the problem of mapping model solution into the problem of optimal matching in the bipartite graph, and verify the performance of our algorithm by contrast experiment. In particular, the fair performance of our algorithm for server-side is over 84%.