基于云环境的高效任务调度算法

高效的任务调度是云服务提供商高效处理业务并降低运营成本的关键。针对云环境下的任务调度问题,提出一种贪心模拟退火的新型算法。首先,利用贪心算法求出局部最优解,并用它来初始化所提新型算法的当前最优解及模拟退火算法的初始解；然后,采用模拟退火算法来不断更新当前最优解。实验结果表明,与传统调度算法相比,所提算法能够更快地达到全局收敛,并得到更加稳定的寻优结果,提高了寻优的质量和效率；同时,该算法不仅减少了总任务时间开销,而且使虚拟机的平均资源利用率稳定在99%以上,负载也更加均衡。

Efficient Task Scheduling Algorithm Based on Cloud Environment

Efficient task scheduling is crucial in dealing with business efficiently and cutting down the operating costs for cloud service providers.To improve the performance of task scheduling in cloud environment,this paper proposed a new algorithm,namely greedy simulated annealing (G&SA).Firstly,it finds the local optimal solution by executing the greedy algorithm,which is used to initialize the current optimal solution of the G&SA algorithm and the initial solution of simulated annealing algorithm.Secondly,the current optimal solution is updated by simulated annealing algorithm.As a result,the experiment shows that the G&SA algorithm can achieve global convergence faster compared with the traditional task scheduling algorithm.In addition,the G&SA algorithm not only obtains more stable optimization results and improves the quality and efficiency of optimization,but also reduces the total task time costs.Average resource utilization rate of virtual machine is steady at 99% or more,and the load can be more balanced.