Abstract
If we choose to compare computing technology to coral reef then cloud computing technology is its very live and growing end. Its challenges are new and demand innovative measure to bring the size of its expending data centers under calipers and bridle its energy consumptions. Reduction in the consumption of energy is to be brought about without compromising quality-of-service and efficacy. For this, we purpose a Hypercube based Genetic Algorithm (HBGA) for efficient VM migration for energy reduction in cloud computing under QoS (Quality-of-service) constraint. The proposed HBGA technique can be implemented in two phases. First, in a data center the physical machines organize themselves in such a way as to acquire a highly scalable structure called Hypercube. The hypercube imperceptibly grates itself up or dips low in sympathy with VM instances as they mount up or get depleted. Secondly on the basis of this representation model of the compute nodes, and given the hypercube topology in which they are organized we propose three algorithms: (a)Hypercube based Node Selection Algorithm to minimize energy consumption (b) Hypercube based VM Selection Algorithm which minimizes the number of VM to be migrated. (c) To solve the problem of VM Placement we propose Hypercube based Genetic algorithm.Experimental results of comparisons between the proposed HBGA method viz-a-viz the existing solutions show a marked reduction in energy consumption of cloud computing environment.
Highlights
The concept of Cloud Computing was first propounded by John McCathy way back in 1961, wherein he envisaged the idea of computer time sharing technology
The proposed Hypercube based Genetic Algorithm (HBGA) technique can be implemented in two phases: Phase I First, in a data center the computer nodes organize themselves in such a way as to acquire a highly scalable structure called hypercube
It is achieved by defining the thresholds of resource utilization based on the Type of load to the Physical machine (PM).As the virtual machines (VMs) migration time is linked with QoS of the cloud application for this we suggest a Hypercube based VM Selection Algorithm based on time space viz. minimum migration time policy which minimizes the number of VM to be migrated.To solve the problem of VM placement we propose Hypercube based Genetic algorithm
Summary
The concept of Cloud Computing was first propounded by John McCathy way back in 1961, wherein he envisaged the idea of computer time sharing technology. His ideas and concept grew with time to become a reality. As they say nothing is beyond human contrivance and utilitarian aspects always egg man to strive for excellence. A single Physical machine (PM) can virtualizes multiple independent virtual machines (VMs) and provide different services. It is like working through ghost machines
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