Resource Scheduling Algorithm in Embedded Cloud Computing and Application

In order to make the embedded cloud computing resources to achieve efficient and real-time task scheduling, this paper puts forward a method of resource scheduling that task completion time and resource load balancing degree as the objective function and using multi-objective particle swarm optimization algorithm to optimize the task scheduling. Simulation results verify the effectiveness of the algorithm, and Applied to a embedded cloud control and measurement system in one oilfield, the results show that this system whose resource scheduling based on multi-objective particle swarm optimization algorithm can meet the real-time requirement of the practical application, and has good practicability.