SDN dynamic flow scheduling algorithm based on discrete particle swarm

Aiming at the problem of unreasonable traffic path allocation in data center networks, which easily leads to large flow conflicts, a software defined network (SDN) traffic scheduling algorithm based on discrete particle swarm is proposed. The algorithm redefines the solution search process within the particle swarm, aims to optimize network performance, dynamically allocates the optimal path for the traffic in the data center to reduce large flow conflicts; and introduces Metropolis to design diversified optimal scheduling schemes to ensure the reasonable scheduling of data center traffic. The experimental results of comparison and verification with other traffic scheduling algorithms show that the algorithm improves network quality, reduces large flow delay, and achieves better load balancing.

Authors

Publication Details

Journal
Scientific insights and discoveries review
Published
2024-09-26
DOI
https://doi.org/10.59782/sidr.v1i1.36
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SDN dynamic flow scheduling algorithm based on discrete particle swarm

Wei Liu, Xincheng Gao, Lili Wang, Qilong Wang et al.
Scientific insights and discoveries review
Software-Defined Networks and 5G
article

SDN dynamic flow scheduling algorithm based on discrete particle swarm

Wei Liu, Xincheng Gao, Lili Wang, Qilong Wang, Xuan Zhang
article en

Abstract

Aiming at the problem of unreasonable traffic path allocation in data center networks, which easily leads to large flow conflicts, a software defined network (SDN) traffic scheduling algorithm based on discrete particle swarm is proposed. The algorithm redefines the solution search process within the particle swarm, aims to optimize network performance, dynamically allocates the optimal path for the traffic in the data center to reduce large flow conflicts; and introduces Metropolis to design diversified optimal scheduling schemes to ensure the reasonable scheduling of data center traffic. The experimental results of comparison and verification with other traffic scheduling algorithms show that the algorithm improves network quality, reduces large flow delay, and achieves better load balancing.

Scientific insights and discoveries reviewVol. 1(1)
Openalex Percentile: Top 82%
Software-Defined Networks and 5G
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.