Cloud Computing Task Scheduling Based on Pheromone Dynamic Adaptive Ant Colony Optimization
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DOI: 10.23977/iceccs.2018.029
Author(s)
Junwei Ge, Yang Liu and Yiqiu Fang
Corresponding Author
Junwei Ge
ABSTRACT
Cloud computing is an Internet-based computing method that provides computers and other devices with shared software and hardware resources and information on the Internet according to their demands. Task scheduling is a core issue of cloud computing. Aiming at the resource scheduling problem of cloud computing, a task scheduling model of DQACO is proposed by improving the pheromone Q in the traditional ant colony optimization. Experiments show that the DQACO algorithm performs better in task completion time and can achieve better scheduling of tasks in the cloud environment.
KEYWORDS
Cloud computing, Ant colony optimization, Task scheduling, Task completion time