Energy-Aware Cooperative Offloading Framework for Inter-dependent and Delay-sensitive Tasks.

Computation offloading is one of the main use-cases of the Multi-access Edge Computing (MEC) paradigm which can help to save the battery life of the resource-poor mobile devices by transferring the computation-intensive tasks to the resource-rich edge cloud servers. However, the ever-increasing internet traffic can negate this benefit due to possible failures of the MEC servers. On the other hand, the growth of computation capabilities of end devices as the result of recent developments of Central Processing Units (CPUs), can help to enhance the MEC systems performance and broaden the concept of edge computing by using device to device communication (D2D). The majority of existing works on computation offloading assume the tasks are independent and can be executed in parallel; however, the dependency among tasks can introduce new problems. To investigate this issue, in this paper, we consider a basic three-node MEC system consists of a user node with sequentially-dependent tasks, a helper/relay node, and a MEC server located at the base station (BS). We formulate the offloading problem into an energy-efficiency minimization problem while satisfying the task-dependency and completion deadline requirements. The simulation results show the superior performance of our proposed method compared to the other approaches.