QoE Aware and Cell Capacity Enhanced Computation Offloading for Multi-Server Mobile Edge Computing Systems with Energy Harvesting Devices

The increasing complexity of intelligent services requires new paradigm to overcome the problems caused by resource-limited mobile devices. Mobile edge computing systemwith energy harvesting devices is such a promising technology. By offloading the computation tasks to the MEC servers, users could experience services with low latency. In addition, energy harvesting technology releases the tension between high energy consumption of intelligent services and capacity-constrained mobile device batteries. However, in multi-user and multi-server scenarios where mobile devices can move arbitrarily, computation offloading strategies are faced with new challenges because of resource competition and server selection. In this paper, we develop an intelligent computation offloadingstrategy. An online algorithm, which is based on Lyapunov Optimization-based Dynamic Computation Offloading algorithm, is proposed. By choosing the execution mode among local execution, offloading execution and task dropping for each mobile device, our algorithm can asymptotically obtain the optimal results for the whole system. The algorithm not only inherits every advantage from the LODCO Algorithm but also adaptsperfectly to themore complex environment.Simulation results illustrate that the algorithmcanimprove the ratio of offloading computation tasks by more than 10% while the QoE is guaranteed.