Implementation of modified overload detection technique with VM selection strategies based on heuristics and migration control

Due to the fast growing computing need catered by Cloud infrastructure, energy consumption reduction has been an active field of research. Dynamic VM consolidation is one such research area where server load is monitored and intelligent decision is taken to optimize the usage of datacenters. In our research, we have designed an overload detection method and several VM selection methods for VM migration to achieve the trade off in VM consolidation. We have redesigned and updated an existing overload detection algorithm using heuristics and implement it in our new VM selection algorithms combining migration control and heuristics that was introduced in[9,10]. We have evaluated our algorithms through simulation on large-scale experiments driven by real-world workload traces from more than a thousand Planet lab VMs. From the comparison with existing energy aware VM consolidation methods, it is found that performance of proposed method incurs least energy consumption.