An Approach to Optimized Resource Scheduling Algorithm for Open-Source Cloud Systems

Based on the deep research on Infrastructure as a Service (IaaS) cloud systems of open-source, we propose an optimized scheduling algorithm to achieve the optimization or sub-optimization for cloud scheduling problems. In this paper, we investigate the possibility to allocate the Virtual Machines (VMs) in a flexible way to permit the maximum usage of physical resources. We use an Improved Genetic Algorithm (IGA) for the automated scheduling policy. The IGA uses the shortest genes and introduces the idea of Dividend Policy in Economics to select an optimal or suboptimal allocation for the VMs requests. The simulation experiments indicate that our dynamic scheduling policy performs much better than that of the Eucalyptus, Open Nebula, Nimbus IaaS cloud, etc. The tests illustrate that the speed of the IGA almost twice the traditional GA scheduling method in Grid environment and the utilization rate of resources always higher than the open-source IaaS cloud systems.