Differential Evolution Algorithm for Optimizing Virtual Machine Placement Problem in Cloud Computing
Author(s) -
Amol C. Adamuthe,
Jayshree T. Patil
Publication year - 2018
Publication title -
international journal of intelligent systems and applications
Language(s) - English
Resource type - Journals
eISSN - 2074-9058
pISSN - 2074-904X
DOI - 10.5815/ijisa.2018.07.06
Subject(s) - computer science , cloud computing , virtual machine , differential evolution , algorithm , load balancing (electrical power) , resource (disambiguation) , data center , evolutionary algorithm , distributed computing , mathematical optimization , artificial intelligence , operating system , computer network , mathematics , geometry , grid
Primary concern of any cloud provider is to improve resource utilization and minimize cost of service. Different mapping relations among virtual machines and physical machines effect on resource utilization, load balancing and cost for cloud data center. Paper addresses the virtual machine placement as optimization problem with resource constraints on CPU, memory and bandwidth. In experimentations, datasets are formed using random data generator. Paper presents random fit algorithm, best fit algorithm based on resource wastage and an evolutionary algorithmDifferential Evolution. Paper presents results of Differential Evolution algorithm with three different mutation approaches. Results show that Differential Evolution algorithm with DE/best/2 mutation operator works efficient than basic DE, best fit and random fit algorithms.
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