Title :
Scheduling of Independent Tasks in Cloud Computing Using Modified Genetic Algorithm
Author :
Singh, Shekhar ; Kalra, Mala
Author_Institution :
Dept. of Comput. Sci., NITTTR, Chandigarh, India
Abstract :
Cloud computing is a provider of dynamic services which offers readily elastic on demand computing resources as per the customer´s request in economical way. As there are a lot of requests fabricated by cloud users which are processed by the accessible resources, there exists a need for better and effective scheduling mechanism for efficient allocation of resources. In this paper, a genetic algorithm based scheduling approach is proposed in which initial population is generated with advance version of Max Min by which we can get more optimize results, in terms of make span. The performance of the proposed Modified Genetic Algorithm (MGA) and existing algorithms have been evaluated against the sample data. Experimental results show that proposed algorithm exhibits acceptable performance and outperforms the existing algorithms.
Keywords :
cloud computing; genetic algorithms; minimax techniques; cloud computing; max min; modified genetic algorithm; task scheduling approach; Biological cells; Cloud computing; Genetic algorithms; Processor scheduling; Scheduling; Sociology; Statistics; Cloud computing; Genetic Algorithm (GA); Modified Genetic Algorithm (MGA); Task Scheduling;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2014 International Conference on
Print_ISBN :
978-1-4799-6928-9
DOI :
10.1109/CICN.2014.128