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Task Scheduling of an Improved Cuckoo Search Algorithm in Cloud Computing

Volume 15, Number 7, July 2019, pp. 1965-1975
DOI: 10.23940/ijpe.19.07.p24.19651975

Wenli Liu, Cuiping Shi, Hongbo Yu, and Hanxiong Fang

Qiqihar University, Qiqihar, 161006, China


(Submitted on March 18, 2019; Revised on May 15, 2019; Accepted on June 15, 2019)


In view of the low efficiency of task scheduling in cloud computing, this paper introduces the cuckoo algorithm to optimize task scheduling. Firstly, the cloud computing task scheduling model is established. Secondly, the particle swarm algorithm and quantum algorithm are introduced for the short search ability of the cuckoo algorithm and the low precision of optimization. The cuckoo is fixed as a "particle" in the search direction in three-dimensional space, so that it cannot be randomly offset. Through the binary algorithm, the particle can be made faster by having the Levy flight randomly generate the step size. The optimal solution direction moves, which speeds up the convergence speed of the algorithm and avoids the blindness in the search process. By using four classical benchmark functions, the simulation results show that the improved algorithm has better performance and improves the efficiency of task scheduling and scheduling under cloud computing.


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