A correlation-based investigation of VM consolidation for cloud computing. (7th July 2022) - Khattar, Nagma; Singh, Jaiteg; Sidhu, Jagpreet
Virtual machine consolidation is of utmost importance in maintaining energy efficient cloud data centres. Tremendous amount of work is listed in literature for various phases of virtual machine consolidation (host underload detection, host overload detection, virtual machine selection and virtual machine placement). Benchmark algorithms proposed by pioneer researchers always cater as a base to develop other optimised algorithms. It seems essential to understand the behaviour of these algorithms for VM consolidation. There is a lack of analysis on these base techniques which otherwise can lead to more computationally intensive and multidimensional solution. The requirement to crucially investigate behaviour of these algorithms under various tunings, parameters and workloads is the need of the hour. This paper addresses the gap in literature and analyses the characteristics of these algorithms in-depth under various scenarios (workloads, parameters) to find the behavioural patterns of algorithms. This analysis also helps in identifying strength of relationship and correlation among parameters. Future research strategy to target the VM consolidation in cloud computing is also proposed.