VRAA: virtualized resource auction and allocation based on incentive and penalty

Authors:
Congfeng Jiang;Liangcheng Duan;Chunlei Liu;Jian Wan;Li Zhou
Affiliations:
School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China 310037;School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China 310037;Department of Mathematics and Computer Science, Valdosta State University, Valdosta, USA 31698;School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China 310037;School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China 310037
Venue:
Cluster Computing
Year:
2013

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Abstract

Virtualization is widely used in cloud computing environments to efficiently manage resources, but it also raises several challenges. One of them is the fairness issue of resource allocation among virtual machines. Traditional virtualized resource allocation approaches distribute physical resources equally without taking into account the actual workload of each virtual machine and thus often leads to wasting. In this paper, we propose a virtualized resource auction and allocation model (VRAA) based on incentive and penalty to correct this wasting problem. In our approach, we use Nash equilibrium of cooperative games to fairly allocate resources among multiple virtual machines to maximize revenue of the system. To illustrate the effectiveness of the proposed approach, we then apply the basic laws of auction gaming to investigate how CPU allocation and contention can affect applications' performance (i.e., response time), and its effect on CPU utilization. We find that in our VRAA model, the fairness index is high, and the resource allocation is closely proportional to the actual workloads of the virtual machines, so the wasting of resources is reduced. Experiment results show that our model is general, and can be applied to other virtualized non-CPU resources.