Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (9): 2534-2543.doi: 10.23940/ijpe.19.09.p27.2534-2543

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ACO-SOS-based Task Scheduling in Cloud Computing

Yuxia Li*   

  1. Beijing Union University, Beijing, 100025, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: *. Yuxia Li is an associate professor at Beijing Union University. She received her master's degree from Beijing Institute of Technology. Her research interests include cloud computing. E-mail address:

Abstract: In order to improve the low task scheduling efficiency of the traditional ant colony algorithm in cloud computing, this paper introduces the symbiotic algorithm into the ant colony algorithm. Firstly, the ant colony algorithm is broken down into two subgroups, and the symbiosis, cohabitation, and parasite mechanisms in the symbiotic algorithm are used to prevent the algorithm from getting into a local optimum and speed it up to obtain the optimal solution. As a result, the cloud computing scheduling simulation results show that the ant colony algorithm-symbiotic algorithm has good performance in terms of virtual machine load balancing, task completion time, and task completion cost, proving that the proposed algorithm can effectively improve the efficiency of cloud computing task scheduling.

Key words: cloud computing, ant colony algorithm, symbiotic algorithm