Heuristic Task Scheduling Algorithm Based on Rational Ant Colony Optimization

Distributed data stream processing system is NP-complete problem to assign tasks to any number of nodes handling the task scheduling. Even for substan- tially reducing scheduling scale, the problem still cannot be avoided. This paper takes advantage of the classical al- gorithm (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 sub- optimal solution of the global task scheduling. The exper- iments show that the data stream processing system we proposed has good real-time characteristics and stability.