JSW 2013 Vol.8(2): 480-487 ISSN: 1796-217X
doi: 10.4304/jsw.8.2.480-487
doi: 10.4304/jsw.8.2.480-487
Survey on Resource Allocation Policy and Job Scheduling Algorithms of Cloud Computing
Lu Huang, Hai-shan Chen, Ting-ting Hu
Software School of Xiamen University, Xiamen, China
Abstract—Cloud computing is the product of the evolution of calculation. It is a new distributed computing model. As more and more people put into the research and applications on cloud computing, the technology of computing becomes more and more widely used. Cloud computing has a huge user group. It has to deal with a large number of tasks. How to make appropriate decisions when allocating hardware resources to the tasks and dispatching the computing tasks to resource pool has become the main issue in cloud computing. This paper is based on the current situation of resource allocation policy and job scheduling algorithms under cloud circumstance. It summarizes some methods to improve the performance, including dynamic resource allocation strategy based on the law of failure, dynamic resource assignment on the basis of credibility, ant colony optimization algorithm for resource allocation, dynamic scheduling algorithm based on threshold, optimized genetic algorithm with dual fitness and improved ant colony algorithm for job scheduling.
Index Terms—Cloud Computing, Resource Allocation, Job Scheduling, Ant Colony Algorithm, Genetic Algorithm.
Abstract—Cloud computing is the product of the evolution of calculation. It is a new distributed computing model. As more and more people put into the research and applications on cloud computing, the technology of computing becomes more and more widely used. Cloud computing has a huge user group. It has to deal with a large number of tasks. How to make appropriate decisions when allocating hardware resources to the tasks and dispatching the computing tasks to resource pool has become the main issue in cloud computing. This paper is based on the current situation of resource allocation policy and job scheduling algorithms under cloud circumstance. It summarizes some methods to improve the performance, including dynamic resource allocation strategy based on the law of failure, dynamic resource assignment on the basis of credibility, ant colony optimization algorithm for resource allocation, dynamic scheduling algorithm based on threshold, optimized genetic algorithm with dual fitness and improved ant colony algorithm for job scheduling.
Index Terms—Cloud Computing, Resource Allocation, Job Scheduling, Ant Colony Algorithm, Genetic Algorithm.
Cite: Lu Huang, Hai-shan Chen, Ting-ting Hu, "Survey on Resource Allocation Policy and Job Scheduling Algorithms of Cloud Computing," Journal of Software vol. 8, no. 2, pp. 480-487, 2013.
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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