In this paper, we consider a two-user mobile-edge computing (MEC) network, where each wireless device (WD) has a sequence of tasks to execute. In particular, we consider task dependency between the two WDs, where the input of a task at one WD requires the final task output at the other WD. Under the considered task-dependency model, we study the optimal task offloading policy and resource allocation (on offloading transmit power and local CPU frequencies) that minimize the weighted sum of the WDs' energy consumption and execution time. The problem is challenging due to the combinatorial nature of the offloading decision among all tasks and the strong coupling with resource allocation among subsequent tasks. When the offloading decision is given, we obtain the closed-form expressions of the offloading transmit power and local CPU frequencies and propose an efficient method to obtain the optimal solutions. Furthermore, we prove that the optimal offloading decision follows an one-climb policy, based on which a reduced-complexity algorithm is proposed to obtain the optimal offloading decision in polynomial time. Numerical results validate the effectiveness of our proposed methods.
When the computing tasks at different MUs have inputoutput dependency, REF studies the optimal binary offloading strategy and resource allocation that minimizes the computation delay and energy consumption.
Optimal Offloading and Resource Allocation in Mobile-Edge Computing with Inter-User Task Dependency
2018 IEEE Global Communications Conference (GLOBECOM)
2018 IEEE Global Communications Conference (GLOBECOM)
Computer Science