Data center flow scheduling method based on differential evolution fusion particle swarm optimization

By using the PSODE algorithm in the data center network combined with the SDN control plane, the problems of link congestion and delay degradation in high-load scenarios are solved, link load balancing and delay control are realized, and network performance is improved.

CN120301835APending Publication Date: 2025-07-11CHONGQING UNIV OF POSTS & TELECOMM
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Patent Information

Application Number
CN202510439564.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-09
Publication Date
2025-07-11

AI Technical Summary

Technical Problem

The existing data center traffic scheduling methods are difficult to adapt to dynamically changing network environments under high load scenarios, resulting in low resource utilization, poor load balancing, link congestion and delay degradation problems.

Method used

The data center traffic scheduling method based on the differential evolution fusion particle swarm algorithm (PSODE) is adopted, combined with the SDN centralized control plane to realize visual monitoring of the traffic state of the entire network, and the optimal path planning under multi-constraint conditions is carried out through an improved metaheuristic algorithm. The complementary characteristics of the particle swarm algorithm and the differential evolution algorithm are used to design a serial hybrid strategy, dynamically trigger differential evolution operations, and optimize link load and delay.

Benefits of technology

It improves link load balancing and delay control of data center networks in high-load scenarios, improves overall network performance, and realizes optimization of link utilization and reduction of delay.

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Abstract

The invention belongs to the technical field of networks, and particularly relates to a data center flow scheduling method based on differential evolution fusion particle swarm optimization, which comprises the following steps that: a switch receives a data flow and judges whether a destination address of the data flow belongs to a local direct connection host, if so, the data flow is forwarded; otherwise, judging the size of the data stream, and if the data stream is a small data stream, scheduling the data stream through an ECMP algorithm, directly distributing a path and issuing a flow table; if the data stream is a big data stream, calculating an optimal path by adopting a PSODE algorithm, optimizing a link load and time delay according to the optimal path, and issuing path information to a switch to execute scheduling; according to the method, the advantages of the SDN and the heuristic algorithm are combined, link load balancing optimization and time delay control are realized in a data center network traffic high-load scene, and the overall performance of the network is further improved.
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