Proceedings Article10.1145/2345396.2345420
Scheduling using improved genetic algorithm in cloud computing for independent tasks
Pardeep Kumar,Amandeep Verma +1 more
- 03 Aug 2012
- pp 137-142
96
TL;DR: The three scheduling techniques Min-Min, Max-Min and Genetic Algorithm have been discussed and performance metrics of Min- Min andMax-Min have been shown and the performance of the standard Genetic Al algorithm and the proposed Improved Genetic Algorithms have been checked against the sample data.
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Abstract: 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.
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References
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TL;DR: Though GA is designed to solve combinatorial optimization problem, it's inefficient for global optimization, so this paper concludes with further researches in optimized genetic algorithm.
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Xu Wang,Beizhan Wang,Jing Huang +2 more
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TL;DR: This paper described what is cloud computing and took Google's cloud computing techniques as an example, summed up key techniques, such as data storage technology, data management technology, and programming model and task scheduling model, used in cloud computing, and some example of cloud computing vendors were illustrated and compared.
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Genetic simulated annealing algorithm for task scheduling based on cloud computing environment
Guo-ning Gan,Ting-lei Huang,Shuai Gao +2 more
- 03 Dec 2010
TL;DR: An optimized algorithm for task scheduling based on genetic simulated annealing algorithm in cloud computing and its implementation, which efficiently completes tasks scheduling in the cloud computing environment computing.
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An optimistic job scheduling strategy based on QoS for Cloud Computing
Qi-yi Huang,Ting-lei Huang +1 more
- 03 Dec 2010
TL;DR: Research on scheduling model from the user's perspective of the Cloud Computing promoted by the business rather than academic which determines its focus on user applications is conducted.
67
Cloud Computing—Task scheduling based on genetic algorithms
Eleonora Maria Mocanu,Mihai Florea,Mugurel Ionut Andreica,Nicolae Tapus +3 more
- 19 Mar 2012
TL;DR: The goal of this project is to improve Hadoop's functionality by implementing a scheduler based on a genetic algorithm, solving the stated problem.
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