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Research of Resource Scheduling based on ACA-GA in the Cloud Computing
Author(s) -
Xuan Chen,
Wenfei Song,
Zhaoguo Li
Publication year - 2016
Publication title -
international journal of grid and distributed computing
Language(s) - English
Resource type - Journals
eISSN - 2207-6379
pISSN - 2005-4262
DOI - 10.14257/ijgdc.2016.9.6.01
Subject(s) - computer science , cloud computing , scheduling (production processes) , distributed computing , operating system , mathematical optimization , mathematics
How to better conduct research resource scheduling has long been a research direction of cloud computing. This paper, aiming at slow convergence and easiness of falling local optimum of ant colony algorithm,has integrated genetic algorithm into the ant colony algorithm and obtained hybrid algorithm (ACA -GA); in the initial solution of the ant colony algorithm, it has adopted selection, crossover and mutation operations of genetic algorithm to obtain an effective initial solution; secondly, it has used the perception threshold of ant colony algorithm path setting to regulate individual selection optimal path; finally, it has improved volatile factor so as to significantly improve the updating efficiency of pheromone. The algorithm in the paper proved that the performance of the algorithm has been also significantly improved through classical test functions. Cloudsim platform shows that, the algorithm above mentioned reduces the time and cost spent in resource scheduling of, hence has some promotional value.

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