A Resource Collaborative Scheduling Strategy Based on Cloud Edge Framework

In recent years, based on cloud-side collaboration scenarios, in order to solve the problem of insufficient device resource storage, computing capacity, and energy efficiency on the cloud side or on the side, cloud-side scheduling policy generation has been introduced in the cloud-side collaboration framework, and computing offloading has been completed on the side. Computing offloading based on cloud-side collaboration can be roughly divided into offloading decision-making and resource allocation. The unloading decision includes which resources to unload, how to unload, and the strategy of computing power allocation; resource allocation is a matter of choosing the destination of resource unloading. The cloud edge collaboration traditional scheme adopts: optimize the corresponding unloading strategy, customize the corresponding resource allocation mechanism, and finally optimize the unloading plan. The main problems are low unloading efficiency and single optimization index. It is more based on traditional sorting algorithms and prioritized according to tasks. Levels are scheduled in the message queue, and optimization solutions are weighed based on one or two indicators of delay, cost, energy consumption, and load balancing. It is urgent to find a multi-objective optimization offloading solution based on a heuristic algorithm in the cloud-side collaboration scenario.