Efficient Mobile Edge Computing with Different Memory Capacities for Mobile Internet of Things

We study the efficient mobile edge computing with different memory capacity (EMEC-DM) problem for a joint computing to process a task both locally and remotely with the objective of minimizing the finishing time. When the task is processed remotely, the time will include the communication and computing time with the storage constraint at the edge. We first describe the time and capacity model, formulate EMEC-DM, prove the NP-completeness, and show the lower bound. We then provide an approximation algorithm, named Computing Partition Approximation (CPA). Numerical results show that the total data length has great impact on the time for mobile edge computing while the movement affects the gateway selection. Numerical results also demonstrate that our algorithm obtains the finishing time close to the optimal solution.