A private cloud instances placement algorithm based on maximal flow algorithm

With the continuous development of cloud computing, bigger and bigger data processing run in the cloud computing environment. In generally, large companies or organizations have the demand of big data processing. However, these companies or organizations do not want to expose their business processes and data to third parties (Amazon, Google, etc.). The private cloud could meet their needs. In private cloud, if the instances of disk resource consuming are placed in the same physical node, clearly, the disk I/O bandwidth would be used up quickly that would affect the performance of the entire node seriously. In this paper, we propose an instances placement algorithm FFDL that based on the maximal flow method and would adopt the disk I/O load balancing strategy and reduce competition for the disk I/O bandwidth between instances. We have validated our approach by conducting a performance evaluation study on the open source privates cloud platform - OpenStack. The results demonstrate that our algorithm has immense potential as it provides significant savings in computation time than the Greedy algorithm and demonstrates high potential for the improvement of disk I/O load balancing in the entire private cloud system for the big data processing.