MOEAGAC:an energy aware model with genetic algorithm for efficient scheduling in cloud computing

作     者：Nageswara Prasadhu Marri N.R.Rajalakshmi 

作者机构：CSEVel Tech Rangarajan Dr Sagunthala R&D Institute of Science and TechnologyChennaiIndia 

出 版 物：《International Journal of Intelligent Computing and Cybernetics》 (智能计算与控制论国际期刊（英文）)

年 卷 期：2022年第15卷第2期

页      面：318-329页

核心收录：

学科分类：08[工学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0713[理学-生态学] 

主　　题：Cloud computing Priority Roulette wheel selection Genetic algorithm Population 

摘      要：Purpose-Majority of the research work either concentrated on the optimization of scheduling length and execution cost or energy optimization *** research aims to propose the optimization of makespan,energy consumption and data transfer time(DTT)by considering the priority *** research work is concentrated on the multi-objective approach based on the genetic algorithm(GA)and energy aware model to increase the efficiency of the task ***/methodology/approach-Cloud computing is the recent advancement of the distributed and cluster *** computing offers different services to the clients based on their requirements,and it works on the environment of *** environment contains the number of data centers which are distributed *** challenges faced by the cloud environment are energy consumption of the data *** scheduling mechanism is needed to allocate the tasks to the virtual machines which help in reducing the *** paper concentrated on the minimizing the consumption of energy as well as makespan value by introducing the hybrid algorithm called as multi-objective energy aware genetic *** algorithm employs the scheduling mechanism by considering the energy consumption of the CPU in the virtual *** energy model is developed for picking the task based on the fitness *** simulation results show the performance of the multi-objective model with respect to makespan,DTT and energy ***-The energy aware model computes the energy based on the voltage and frequency distribution to the CPUs in the virtual *** directed acyclic graph is used to represent the task *** proposed model recorded 5% less makespan compared against the MODPSO and 0.7% less compared against the HEFT *** proposed model recorded 125 joules energy consumption for 50 VMs when all are in active ***/value-This paper proposed the multi-