基于多维评价模型及改进蚁群优化算法的云计算资源调度策略

针对云计算环境下资源调度模型未充分考虑资源评价的问题，为更好适应不同节点计算性能和大规模数据环境的处理需求，提出了一种基于多维评价模型的虚拟机资源调度策略。首先，在云计算环境下建立包括网络性能在内的多维资源评价模型，在此基础上提出一种改进的蚁群优化算法实现资源调度策略；然后在云计算仿真平台CloudSim上进行实现。实验结果表明，该算法可以更好适应不同网络性能的计算环境，显著提高了资源调度的性能，同时降低了虚拟机负载均衡离差，满足了云计算环境下的虚拟机资源负载均衡需求。

Cloud Computing Resource Scheduling Strategy Based on Multidimensional Evaluation Model and Improved Ant Colony Algorithm

Aiming at the resource scheduling model fails to fully consider the resorce assessment in cloud computing environment, a virtual machine resource scheduling strategy based on multi-dimension evaluation model is Proposed to better adapt to the demand for computing performance and large data environment for different node processing. First of all, establish the evaluation model of multidimensional resources include network performance in the cloud computing environment, on this basis proposed an improved ant colony optimization algorithm for resource scheduling strategy; And then realized on the simulation platform of CloudSim. The experiment shows the algorithm in this paper can better adapt to different computing environments of network performance, significantly improve the performance of resource scheduling, and reduce the load balance deviation, meet the virtual machine resource in the cloud computing environment load balancing demand.