Topology-Aware Partial Virtual Cluster Mapping Algorithm on Shared Distributed Infrastructures

Novel virtualized HPC centers provide isolated and configurable Virtual Clusters (VC) on shared distributed infrastructures as execution environments for parallel and distributed applications. These VCs are usually customized and deployed per job in runtime. Allocating physical resources for VC is known as Virtual Cluster Mapping (VCM) problem, which is a critical issue that affects both performance of the VC and resource utilization of the system. Most previous works treat all Virtual Machines (VMs) in a VC request equally. However, because sub-jobs in a parallel job usually perform different roles, the corresponding VMs in a VC that execute these sub-jobs respectively should have different levels of importance. Based on this argument, this paper introduces the concept of partial VC mapping in contrast to the full mapping methodology in the current literatures. To fulfill partial mapping, the important backbone communication structure of parallel job called Communication Skeleton (CS) is derived based on the network topology among virtual nodes. To generate the CS of a job, mechanisms for evaluating the importance of nodes are proposed. Eventually, a Topology-aware Partial Virtual Cluster Mapping algorithm (TOP-VCM) is proposed which is based on sub-graph isomorphism detection. TOP-VCM can fully satisfy the nodes/links requirements in CS to ensure the execution performance with only slight degradation of other trivial nodes/links to significantly reduce the mapping difficulty. Simulation results have shown that TOP-VCM has significantly improved the total revenue, the utilization of physical resources and the performance of mapping algorithm while satisfying the VC requirements.