Issue No. 02 - Feb. (2018 vol. 29)
Lei Yu , School of Computer Science, Georgia Institute of Technology, Atlanta, GA
Haiying Shen , Department of Computer Science, University of Virginia, Charlottesville, VA
Zhipeng Cai , Department of Computer Science, Georgia State University, Atlanta, GA
Ling Liu , School of Computer Science, Georgia Institute of Technology, Atlanta, GA
Calton Pu , School of Computer Science, Georgia Institute of Technology, Atlanta, GA
In the cloud, multiple tenants share the resource of datacenters and their applications compete with each other for scarce network bandwidth. Current studies have shown that the lack of bandwidth guarantee causes unpredictable network performance, leading to poor application performance. To address this issue, several virtual network abstractions have been proposed which allow the tenants to reserve virtual clusters with specified bandwidth between the Virtual Machines (VMs) in the datacenters. However, all these existing proposals require the tenants to deterministically characterize the bandwidth demands in the abstractions, which can be difficult and result in inefficient bandwidth reservation due to the demand uncertainty. In this paper, we explore a virtual cluster abstraction with stochastic bandwidth characterization to address the bandwidth demand uncertainty. We propose Stochastic Virtual Cluster (SVC), which models the bandwidth demand between VMs in a probabilistic way. Based on SVC, we develop a stochastic framework for virtual cluster allocation, in which the admitted virtual cluster's bandwidth demands are satisfied with a high probability. Efficient VM allocation algorithms are proposed to implement the framework while reducing the possibility of link congestion through minimizing the maximum bandwidth occupancy of a virtual cluster on physical links. Using simulations, we show that SVC achieves the trade-off between the job concurrency and the average job running time, and demonstrate its effectiveness for accommodating cloud application workloads with highly volatile bandwidth demands and its improvement to work-conserving bandwidth enforcement.
Bandwidth, Cloud computing, Resource management, Static VAr compensators, Stochastic processes, Uncertainty, Clustering algorithms
L. Yu, H. Shen, Z. Cai, L. Liu and C. Pu, "Towards Bandwidth Guarantee for Virtual Clusters Under Demand Uncertainty in Multi-Tenant Clouds," in IEEE Transactions on Parallel & Distributed Systems, vol. 29, no. 2, pp. 450-465, 2018.