Running Scientific Computing Workloads in JointCloud Computing Environment

Abstract

Cloud computing has been widely adopted by personal developers and enterprises because of its on-demand and elastic resource usage paradigm. Currently most cloud applications are running on one single cloud. Cloud vendors provide users a bewildering choice of VMs and the choice can have a big impact on performance and cost. Therefore, it is difficult to choose the appropriate VMs to process jobs efficiently and economically. Besides, more and more applications are demanding to run across several clouds with heterogeneous resources to satisfy the requirements like best cost efficiency, avoidance of vender lock-in, and geolocation sensitive service. Existing systems lack a mechanism to unify the management of heterogeneous computing resources across clouds. In this paper, we present Docklet to build a virtual private cloud in JointCloud environments, managing heterogeneous and distributed cloud resources and selecting suitable resources according to the needs of users. At the same time, it provides computing framework support for scientific computing workloads, having the customized software stacks, configurations readily available. With Docklet, users only need one browser to do their jobs online. In the end, we evaluate the performance of running scientific workloads in Docklet.