Resource Virtualization Model Using Hybrid-graph Representation and Converging Algorithm for Cloud Computing

Cloud computing can provide a great capacity for massive computing, storage as well as processing. The capacity comes from the cloud computing system itself, which can be likened to a virtualized resource pool that supports virtualization applications as well as load migration. Based on the existing technologies, the paper proposes a resource virtualization model (RVM) utilizing a hybrid-graph structure. The hybrid-graph structure can formally represent the critical entities such as private clouds, nodes within the private clouds, and resource including its type and quantity. It also provides a clear description of the logical relationship and the dynamic expansion among them as well. Moreover, based on the RVM, a resource converging algorithm and a maintaining algorithm of the resource pool which can timely reflect the dynamic variation of the private cloud and resource are presented. The algorithms collect resources and put them into the private cloud resource pools and global resource pools, and enable a real-time maintenance for the dynamic variation of resource to ensure the continuity and reliability. Both of the algorithms use a queue structure to accomplish functions of resource converging. Finally, a simulation platform of cloud computing is designed to test the algorithms proposed in the paper. The results show the correctness and the reliability of the algorithms.