Improving resource utilization in cloud environments using application placement heuristics

Application placement is an important concept when providing software as a service in cloud environments. Because of the potential downtime cost of application migration, most of the time additional resource acquisition is preferred over migrating the applications residing in the virtual machines (VMs). This situation results in under-utilized resources. To overcome this problem static/dynamic estimations on the resource requirements of VMs and/or applications can be performed. A simpler strategy is using heuristics during application placement process instead of naively applying greedy strategies like round-robin. In this paper, we propose a number of novel heuristics and compare them with round robin placement strategy and a few proposed placement heuristics in the literature to explore the performance of heuristics in application placement problem. Our focus is to better utilize the resources offered by the cloud environment and at the same time minimize the number of application migrations. Our results indicate that an application heuristic that relies on the difference between the maximum and minimum utilization rates of the resources not only outperforms other application placement approaches but also significantly improves the conventional approaches present in the literature.