基于改进的粒子群优化的云计算资源调度模型

针对云计算系统中多任务并发模式下引发的资源竞争，本文提出了一种基于改进的粒子群优化的云计算资源调度分配模型，以提高资源利用率.首先，对云计算系统中的资源调度问题进行形式化描述，构建以任务的总完成时间为优化对象的目标函数.其次，求解时采用粒子群优化算法，为保证收敛速度且避免粒子群在搜索过程中陷入局部最优，定义了惯性权重函数.另外，引入一个调整算子以优化位置更新.仿真结果表明，本文提出的资源调度分配模型能够有效提高云计算资源利用率，大幅减少任务的处理时间.

An improved computing resource scheduling model of cloud computing based on particle swarm optimization

Aiming at the problem of resource competition in the system of traditional cloud computing， an improved computing resource scheduling model of cloud computing based on particle swarm optimization is proposed to improve the utilization rate of resources. Firstly， the resource scheduling problem of cloud computing is formalized， which defines the objective function of optimization object and constructs the total completion time for the tasks. Secondly， the particle swarm optimization is introduced to resolve the above problem， and inertia weight function is defined to keep the particles from swarming into the local optimum under the premise of ensuring the convergence speed. The simulation results show that the proposed resource scheduling model can improve the utilization of cloud computing resources effectively， and reduce the processing time of the task greatly.