Impact of Instance Seeking Strategies on Resource Allocation in Cloud Data Centers

With the prosperity of cloud computing, an increasing number of Small and Medium-sized Enterprises (SMEs) move their business to public clouds such as Amazon EC2. To help tenants deploy services in the cloud, researchers either conduct performance evaluations or design mechanisms and software on seeking virtual machines of better performance. However, few studies have investigated the impact of instance seeking strategies on resource allocation in clouds if every tenant starts to apply the same method to find the better performing virtual machine. In this paper, we propose a cloud and a tenant model in order to simulate the process of tenants' seeking better-performing instances in the cloud. We discuss, implement and evaluate six cloud resource allocation strategies and five instance seeking strategies. We perform the evaluation via simulation based on real data traces. Our results show that instance seeking strategies can cause the exhaustion of better-performing instances and significant request growth in the cloud. Furthermore, we find that tenants could save time and budget through collaborative seeking strategies. Finally, we discuss the implications of our findings from perspectives of both tenants and providers.