A large organization, such as a university, commonly supplies computational power through multiple independently administered computational domains (e.g. clusters). Each computational domain faces the conflict between dynamic workload and static capacity. This is clearly inefficient at times when some clusters have idle nodes while others experience excessive workload. An opportunity arises to resolve this conflict by dynamically adapting the capacity of clusters by borrowing idle machines of peer domains. In this paper, we present the design, implementation, and evaluation of VioCluster, a virtualization based computational resource sharing platform. Through machine and network virtualization, VioCluster enables virtual computational domains that safely “trade” machines between them without infringing on the autonomy of either domain. Our performance evaluation results show that dynamic machine trading between virtual domains increases their resource utilization and decreases ...
Paul Ruth, P. McGachey, Dongyan Xu