Heuristic Task Scheduling Algorithm Based on Rational Ant Colony Optimization

ZHANG Xiaodong; CUI Xiaoyan; ZHENG Shizhuo

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Article Navigation > Chinese Journal of Electronics > 2014 > 23(2): 311-314

ZHANG Xiaodong, CUI Xiaoyan, ZHENG Shizhuo, “Heuristic Task Scheduling Algorithm Based on Rational Ant Colony Optimization,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 311-314, 2014,

Citation:

ZHANG Xiaodong, CUI Xiaoyan, ZHENG Shizhuo, “Heuristic Task Scheduling Algorithm Based on Rational Ant Colony Optimization,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 311-314, 2014,

ZHANG Xiaodong, CUI Xiaoyan, ZHENG Shizhuo, “Heuristic Task Scheduling Algorithm Based on Rational Ant Colony Optimization,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 311-314, 2014,

Citation:

ZHANG Xiaodong, CUI Xiaoyan, ZHENG Shizhuo, “Heuristic Task Scheduling Algorithm Based on Rational Ant Colony Optimization,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 311-314, 2014,

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Heuristic Task Scheduling Algorithm Based on Rational Ant Colony Optimization

1.
School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China;
2.
Automation School, Beijing University of Posts and Telecommunications, Beijing 100876, China

Funds: This work is supported by the International Science and Technology Cooperation Program of China (No.2013DFR10530) and National High-Tech Research and Development Program of China (863 Program) (No. 2011AA01A101).

Received Date: 2013-05-01
Rev Recd Date: 2013-09-01
Publish Date: 2014-04-05

Abstract

Abstract

Distributed data stream processing system is NP-complete problem to assign tasks to any number of nodes handling the task scheduling. Even for substantially reducing scheduling scale, the problem still cannot be avoided. This paper takes advantage of the classical algorithm (ant colony optimization) of heuristic methods to simulate the global task scheduling problem of distributed system. Rational improvement on ant colony optimization path-finding for the memory and CPU usage of each node achieves load balancing in a short time. It gives the suboptimal solution of the global task scheduling. The experiments show that the data stream processing system we proposed has good real-time characteristics and stability.
- Distributed data stream processing system,
- Rational ant colony optimization,
- Heuristic algorithm

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References(11)

References

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