Open AccessAugmented intelligent water drops optimisation model for virtual machine placement in cloud environment
Author(s) -
Eswaran Sivaraman,
Dominic Daniel,
Natarajan Jayapandian,
Honnavalli Prasad B.
Publication year - 2020
Publication title -
iet networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 21
eISSN - 2047-4962
pISSN - 2047-4954
DOI - 10.1049/iet-net.2019.0165
Subject(s) - virtual machine , cloud computing , computer science , distributed computing , process (computing) , ant colony optimization algorithms , resource (disambiguation) , ant colony , operating system , artificial intelligence , computer network
Virtual machine placement in cloud computing is to allocate the virtual machines (VMs) (user request) to suitable physical machines (PMs) so that the wastage of resources is reduced. Allocation of appropriate VMs to suitable and effective PMs will lead the service provider to be a better competitor with more available resources for affording a greater number of VMs simultaneously which in turn reflects with the growth in the economy. In this research work, an augmented intelligent water drop (IWD) algorithm is used for effectively placing VMs. The preliminary goal of this proposed work is to reduce the overall resource utilisation by packing the VMs to appropriate PMs effectively. The proposed IWD model is tested under the standard simulation process as it is given in the literature. Performance of IWD is compared with the existing techniques first fit decreasing, least loaded and ant colony optimisation algorithm. Performance analysis shows the significance of the proposed method over existing techniques.