Hybrid Artificial Bee Colony and Tabu Search Based Power Aware Scheduling for Cloud Computing | Zendy

Priya Sharma | Zendy; Kiranbir Kaur | Zendy

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Hybrid Artificial Bee Colony and Tabu Search Based Power Aware Scheduling for Cloud Computing

Author(s) -

Priya Sharma,

Kiranbir Kaur

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.2018.07.04

Subject(s) - computer science , virtual machine , cloud computing , tabu search , scheduling (production processes) , job shop scheduling , load balancing (electrical power) , distributed computing , task (project management) , artificial intelligence , mathematical optimization , operating system , mathematics , schedule , geometry , management , economics , grid

Load balancing is an important task on virtual machines (VMs) and also an essential aspect of task scheduling in clouds. When some Virtual machines are overloaded with tasks and other virtual machines are under loaded, the load needs to be balanced to accomplish optimum machine utilization. This paper represents an existing technique “artificial bee colony algorithm” which shows a low convergence rate to the global minimum even at high numbers of dimensions. The objective of this paper is to propose the integration of artificial bee colony with tabu search technique for cloud computing environment to enhance energy consumption rate. The main improvement is makespan 28.4 which aim to attain a well balanced load across virtual machines. The simulation result shows that the proposed algorithm is beneficial when compared with existing algorithms.

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