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In this paper, the problem of joint user scheduling and computing resourceallocation in asynchronous mobile edge computing (MEC) networks is studied. Insuch networks, edge devices will offload their computational tasks to an MECserver, using the energy they harvest from this server. To get their tasksprocessed on time using the harvested energy, edge devices will strategicallyschedule their task offloading, and compete for the computational resource atthe MEC server. Then, the MEC server will execute these tasks asynchronouslybased on the arrival of the tasks. This joint user scheduling, time andcomputation resource allocation problem is posed as an optimization frameworkwhose goal is to find the optimal scheduling and allocation strategy thatminimizes the energy consumption of these mobile computing tasks. To solve thismixed-integer non-linear programming problem, the general benders decompositionmethod is adopted which decomposes the original problem into a primal problemand a master problem. Specifically, the primal problem is related tocomputation resource and time slot allocation, of which the optimal closed-formsolution is obtained. The master problem regarding discrete user schedulingvariables is constructed by adding optimality cuts or feasibility cutsaccording to whether the primal problem is feasible, which is a standardmixed-integer linear programming problem and can be efficiently solved. Byiteratively solving the primal problem and master problem, the optimalscheduling and resource allocation scheme is obtained. Simulation resultsdemonstrate that the proposed asynchronous computing framework reduces 87.17%energy consumption compared with conventional synchronous computingcounterpart.

Joint User Scheduling and Computing Resource Allocation Optimization in Asynchronous Mobile Edge Computing Networks