A novel offloading scheduling method for mobile application in mobile edge computing

In mobile edge computing (MEC), task offloading can solve the problem of resource constraints on mobile devices effectively, but it is not always optimal to offload all the computation subtasks of an application. In order to solve the energy and delay of fine-grained offloading in MEC, this paper proposes a novel offloading scheduling based on multi-user fine-grained for IoT. In order to optimize the execution location and scheduling order of subtasks, we regard the computation task as a directed acyclic graph (DAG). Considering the energy consump -tion and delay, the computation offloading is considered as a constrained multi-objective optimization problem (CMOP), and then an improved NSGA-II algorithm is proposed to solve the CMOP. The proposed algorithm can realize local and edge parallel processing, which can effectively reduce the delay and energy consumption. Finally, extensive experiments show that the proposed algorithm is significantly better than the related algorithms in terms of energy and delay. Compared with no-segmentation and related segmentation algorithms, the proposed algorith -m can achieve up 10–50% reduction about energy saving. And the proposed algorithm can make the optimal decision in practical applications.