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Distributed Processing System, 2022, 3(3); doi: 10.38007/DPS.2022.030301.

Distributed System Task Assignment Considering Ant Colony Algorithm


Jian Yang

Corresponding Author:
Jian Yang

College of Electronic Engineering, National University of Defense Technology, Hefei 230031, Anhui, China


In a company of a certain scale, a large number of tasks need to be allocated every day. It is particularly important to provide a comprehensive and efficient distributed system for resource scheduling. Ant colony algorithm (ACO) has great advantages in resource scheduling, so In this paper, the problem of task assignment in distributed systems is studied considering the ant colony optimization algorithm. The structure of this paper can be divided into three parts, including related theoretical overview, system design and system analysis. In the system design and system analysis, through the comparative analysis of the ant colony algorithm (ACO), the ant colony optimization algorithm based on load balancing (LBACO) and the improved ant colony algorithm (IACO), the optimal algorithm is found. Assign tasks.


Ant Colony Algorithm, Distributed System, Task Allocation, Resource Scheduling

Cite This Paper

Jian Yang. Distributed System Task Assignment Considering Ant Colony Algorithm. Distributed Processing System (2022), Vol. 3, Issue 3: 1-8. https://doi.org/10.38007/DPS.2022.030301.


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