Resource Allocation in Cloud Computing Using the Uncertainty Principle of Game Theory

Virtualization of resources on the cloud offers a scalable means of consuming services beyond the capabilities of small systems. In a cloud that offers infrastructure such as processor, memory, hard disk, etc., a coalition of virtual machines formed by grouping two or more may be needed. Economical management of cloud resources needs allocation strategies with minimum wastage, while configuring services ahead of actual requests. We propose a resource allocation mechanism for machines on the cloud, based on the principles of coalition formation and the uncertainty principle of game theory. We compare the results of applying this mechanism with existing resource allocation methods that have been deployed on the cloud. We also show that this method of resource allocation by coalition-formation of the machines on the cloud leads not only to better resource utilization but also higher request satisfaction.

I. Introduction

INFRASTRUCTURE as a service (IaaS) cloud systems offer computational infrastructure services to multiple clients by means of virtual machines (VMs). The recent surge in the popularity of IaaS cloud systems can be attributed to the on-demand availability of computing resources such as processor cores, memory, disks, etc., packages as VMs that are billed on use [1], [2]. At times, the service requirements are such that not all VMs can be hosted on a single machine. Incoming task requests may demand VMs of different capacities as well. In this scenario, coalitions of machines need to be formed to service a particular request [3]. In particular, in IaaS systems, VMs are available in specific configurations that are further customized by clients by adding operating systems and software on top [2]. Coalitions of preconfigured VMs created before the arrival of requests address scalability concerns to a large extent, in addition to shortening response times.