An Efficient Collaborative Algorithm for Building-Wide Mobile Edge Computing

The rapid proliferation of multi-mobile devices in smart building environments has intensified the demand for efficient computation offloading strategies in mobile edge computing. To address the challenges of task offloading, communication, and computation resource allocation while also considering the mobility of mobile devices and task priorities, we design a target server query strategy based on resource matching. This strategy accommodates the varying resource requirements of different task types and avoids increasing algorithm complexity. Based on this strategy, we propose the Greedy-Based Collaborative Algorithm to minimize the average execution time of tasks. Simulation results demonstrate that the proposed algorithm outperforms baseline algorithms and that the energy consumption of mobile devices remains acceptable.