Game-Theory-Based Task Offloading and Resource Scheduling in Cloud-Edge Collaborative Systems

Task offloading and resource allocation are the major elements of edge computing. A reasonable task strategy scheme can reduce processing time save system energy consumption. Most current studies on migration computing only consider between terminals servers, ignoring huge resources in cloud center. In order to sufficiently utilize server resources, we propose a coarse-grained intelligent matching under Cloud-Edge collaboration. We heterogeneity mobile devices inter-channel interference, establish decision multiple end-users as game-theory-based model with objective maximizing utility. addition, an improved particle swarm optimization algorithm obtain strategies. Experimental results show that proposed outperforms other schemes respect latency consumption, it scales well increases number devices.