Cloud Computing Resource Scheduling Optimization Based on Chaotic Firefly Algorithm Based on the Tent Mapping

  • Xiaolan Xie
  • Mengnan QiuEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 950)


In order to improve the utilization of cloud computing resources and maintain the load balance, this paper proposes a cloud computing resource scheduling optimization chaotic firefly algorithm based on the Tent mapping to solve the problem that the firefly algorithm has premature convergence and is easily trapped in the local optimum. In the firefly algorithm, a chaotic algorithm based on the Tent mapping is introduced. By perturbing individuals, the convergence speed is accelerated and the local most optimal probability is reduced. The Bernoulli shift transformation is introduced to improve the cloud computing model. The simulation results based on CloudSim show that the algorithm can shorten the task completion time and improve the overall processing capability of the system.


Firefly algorithm Tent mapping Chaos optimization Cloud computing Resource scheduling CloudSim 



This research work was supported by the National Natural Science Foundation of China (Grant No. 61762031), Guangxi Key Research and Development Plan (No. 2017AB51024, 2018AB8126006), GuangXi key Laboratory Fund of Embedded Technology and Intelligent System.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.College of Information Science and EngineeringGuilin University of TechnologyGuilinChina
  2. 2.Guangxi Universities Key Laboratory of Embedded Technology and Intelligent SystemGuilin University of TechnologyGuilinChina

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