Journal Published Online: 19 August 2022
Volume 51, Issue 3

A Balanced Scheduling Method of Smart City Enterprise Resource Information Based on Improved Ant Colony Algorithm

CODEN: JTEVAB

Abstract

In order to address the problems of low resource utilization rate and poor scheduling balance in current enterprise resource information balanced scheduling, an enterprise resource information balanced scheduling method based on an improved ant colony algorithm (ACO) was proposed. The ACO framework is introduced in this algorithm to establish a balanced scheduling model of enterprise resource information. By adding a mapping algorithm of a virtual machine and physical machine, an improved algorithm of load balancing between nodes is proposed based on the ACO. Forward ants detect node types, record node information, and leave foraging pheromones when they encounter load nodes. The backward ants trace back to the load node according to the tracking pheromone and allocate the overloaded node task reasonably. In the search process, the path pheromone is dynamically modified according to the node type, and the analysis of enterprise resource information balance scheduling algorithm is completed. The experimental results show that this method has good balance of resource information scheduling and can effectively improve resource utilization.

Author Information

Chen, Suqing
Computer and Big Data Department, Jining Normal University, Ulanqab, China
Pages: 12
Price: $25.00
Related
Reprints and Permissions
Reprints and copyright permissions can be requested through the
Copyright Clearance Center
Details
Stock #: JTE20220129
ISSN: 0090-3973
DOI: 10.1520/JTE20220129