A Heuristic Scheduling Strategy for Independent Tasks on Grid
HPCASIA '05 Proceedings of the Eighth International Conference on High-Performance Computing in Asia-Pacific Region
An Improved Genetic Algorithm with Limited Iteration for Grid Scheduling
GCC '07 Proceedings of the Sixth International Conference on Grid and Cooperative Computing
PDCAT '07 Proceedings of the Eighth International Conference on Parallel and Distributed Computing, Applications and Technologies
Independent tasks scheduling based on genetic algorithm in cloud computing
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
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Cloud computing is a new technology and it is becoming popular day by day because of its great features. In this technology almost everything like hardware, software and platform are provided as a service. These services are charged from users on the pay-per-use bases. A cloud provider in cloud computing provides services on the basis of clients' requests. An important issue in cloud computing is the scheduling of users' requests means how to allocate resources to these requests, so that the requested tasks can be completed in a minimum time according to the user defined time. A good scheduling technique also helps in efficient utilization of the resources. Many scheduling algorithms have been researched like Min-Min, Max-Min, X-Sufferage, Genetic Algorithm, Particle Swarm Optimization etc. In this paper the three scheduling techniques Min-Min, Max-Min and Genetic Algorithm have been discussed and performance metrics of Min-Min and Max-Min have been shown. The performance of the standard Genetic Algorithm and the proposed Improved Genetic Algorithm have been checked against the sample data. A new scheduling idea is also proposed in which Min-Min and Max-Min can be combined in Genetic Algorithm.