Task offloading and multi-cache placement in multi-access mobile edge computing

As mobile augmented reality (MAR) applications continue to develop and spread, more and more data-intensive and computationally intensive tasks are sensitive to delay and energy consumption. The emergence of mobile edge computing provides an effective solution for the demand of low latency and low energy consumption. This paper studies the task offloading and multi-cache placement of MAR applications in a three-tier transmission system composed of edge servers, edge data centers and remote cloud. Under the constraint of computing resources and cache space, the task offloading and cache placement problems are formulated to maximize the energy efficiency function including task completion rate and energy consumption. To solve this problem, we design a task offloading and multi-cache placement algorithm based on block coordinate descent. Firstly, we generate the priority queue for the tasks. Then, caches are placed according to the popularity of each cache and the cache space ratio of each edge node. Tasks are offloaded according to the priority of each edge node. After the initialization, the task offloading strategy and cache placement strategy are optimized using block coordinate descent. Finally, we update the optimized cache placement strategy and task offloading strategy until the objective function converges. Simulation results show that our algorithm can significantly shorten service delay and reduce energy consumption compared with other algorithms.