Research on Offloading Strategy in Edge Computing of Internet of Things
Xiaoting Duan, Fei Xu, Yongyong Sun · 2020
Aiming at the problem of tasks offloading strategy and performance optimization in edge computing for Internet of things, this paper studies how to effectively offload applications to achieve the trade-off between offloading cost and system performance. Considering the regional advantages of edge servers and the abundant resources of remote cloud computing center, this paper constructs an optimization model with offloading cost as the optimization objective and queue stability as the constraint condition, and proposes a drift plus cost computing offloading strategy (DCCO) based on Lyapunov optimization. This strategy decomposes the optimization problem into a series of subproblems, and allocates tasks according to the current situation of queue backlog and offloading target nodes, so as to meet the optimization target of users and ensure the stability of the system. Simulation results show that the algorithm effectively reduces the cost of tasks offloading and the increase of queue backlog.