Research on Distributed Computing Power Scheduling Based on Ant Path Optimization

This study solves the problem of data fusion caused by multi-source and cross-domain power business data, proposes a cross-domain computing capability model for the entire network based on the data middle platform, realizes the sharing and computing of multi-source data, and provides a new solution for the challenges of data centers. It also designs a cross-domain computing power scheduling algorithm based on ant path optimization, significantly improves the accuracy and stability of computing power scheduling through heuristic information design, etc. Experimental verification shows that the algorithm is superior to existing distributed scheduling algorithms in terms of scheduling overhead, etc., and is suitable for the multi-source cross-domain data fusion computing scenarios in data centers. The innovation lies in the introduction of the path optimization idea of the ant algorithm, overcomes the problems of traditional scheduling algorithms, and provides examples and method support for the optimization of power data management and distributed data processing technology in other fields.