An Efficient Resource Management System for On-Line Virtual Cluster Provision

As a prevalent paradigm for flexible, scalable and on-demand provisions of computing services, Cloud computing can be an alternative platform for scientific computing. In this paper, we propose an efficient resource management system for on-line virtual clusters provision, aiming to provide immediately-available virtual clusters for academic users. Particularly, we investigated two crucial problems: efficient VM image management and intelligent resource mapping, either of them has remarkable impact on the performance of the system. VM image management includes image preparation and local image management on physical resources. A resource mapping refers to a mapping from userpsilas resource constraints to specific physical resources. We explore how to simplify VM image management and reduce image preparation overhead by the multicast file transferring and image caching/reusing. Additionally, the Load-Aware Mapping, a novel resource mapping strategy, is proposed in order to further reduce deploying overhead and make efficient use of resources. The strategy takes account of both image cache and VM load distribution information. System evaluation is conducted through various real stress workloads, and results show that our approaches are effective comparing to other common solutions.