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Sun, H. (2014) Design of Task-Resource Allocation Model Based on Q-Learning and Double Orientation ACO Algorithm for Cloud Computing. Computer Measurement & Control, 10, 3343-3346.

has been cited by the following article:

• TITLE: The Objective Function Value Optimization of Cloud Computing Resources Security Allocation of Artificial Firefly Algorithm

  AUTHORS: Xiaoxi Hu

  KEYWORDS: Cloud Computing Resources, Security Distribution, Improved Artificial Firefly Algorithm, Complex Method, Local Search Operator

  JOURNAL NAME: Open Journal of Optimization, Vol.4 No.2, May 15, 2015

  ABSTRACT: Based on the current cloud computing resources security distribution model’s problem that the optimization effect is not high and the convergence is not good, this paper puts forward a cloud computing resources security distribution model based on improved artificial firefly algorithm. First of all, according to characteristics of the artificial fireflies swarm algorithm and the complex method, it incorporates the ideas of complex method into the artificial firefly algorithm, uses the complex method to guide the search of artificial fireflies in population, and then introduces local search operator in the firefly mobile mechanism, in order to improve the searching efficiency and convergence precision of algorithm. Simulation results show that, the cloud computing resources security distribution model based on improved artificial firefly algorithm proposed in this paper has good convergence effect and optimum efficiency.