Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm
Software-defined networks (SDNs) are computer networks where parameters and devices are configured by software. Recently, artificial intelligence aspects have been used for SDN programs for various applications, including packet classification and forwarding according to the quality of service (QoS)...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/2/462 |
| _version_ | 1797443379497271296 |
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| author | Rana Fareed Ghani Laith Al-Jobouri |
| author_facet | Rana Fareed Ghani Laith Al-Jobouri |
| author_sort | Rana Fareed Ghani |
| collection | DOAJ |
| description | Software-defined networks (SDNs) are computer networks where parameters and devices are configured by software. Recently, artificial intelligence aspects have been used for SDN programs for various applications, including packet classification and forwarding according to the quality of service (QoS) requirements. The main problem is that when packets from different applications pass through computer networks, they have different QoS criteria. To meet the requirements of packets, routers classify these packets, add them to multiple weighting queue systems, and forward them according to their priorities. Multiple queue systems in routers usually use a class-based weighted round-robin (CBWRR) scheduling algorithm with pre-configured fixed weights for each priority queue. The problem is that the intensity of traffic in general and of each packet class occasionally changes. Therefore, in this work, we suggest using the particle swarm optimization algorithm to find the optimal weights for the weighted fair round-robin algorithm (WFRR) by considering the variable densities of the traffic. This work presents a framework to simulate router operations by determining the weights and schedule packets and forwarding them. The proposed algorithm to optimize the weights is compared with the conventional WFRR algorithm, and the results show that the particle swarm optimization for the weighted round-robin algorithm is more efficient than WFRR, especially in high-intensity traffic. Moreover, the average packet-loss ratio does not exceed 7%, and the proposed algorithms are better than the conventional CBWRR algorithm and the related work results. |
| first_indexed | 2024-03-09T12:56:11Z |
| format | Article |
| id | doaj.art-b16bdfa7b9b14c928d9433495ef74089 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T12:56:11Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-b16bdfa7b9b14c928d9433495ef740892023-11-30T22:00:48ZengMDPI AGElectronics2079-92922023-01-0112246210.3390/electronics12020462Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm AlgorithmRana Fareed Ghani0Laith Al-Jobouri1Department of Computer Science, University of Technology-Iraq, Baghdad 10066, IraqSchool of Design and Informatics, Abertay University, Dundee DD1 1HG, UKSoftware-defined networks (SDNs) are computer networks where parameters and devices are configured by software. Recently, artificial intelligence aspects have been used for SDN programs for various applications, including packet classification and forwarding according to the quality of service (QoS) requirements. The main problem is that when packets from different applications pass through computer networks, they have different QoS criteria. To meet the requirements of packets, routers classify these packets, add them to multiple weighting queue systems, and forward them according to their priorities. Multiple queue systems in routers usually use a class-based weighted round-robin (CBWRR) scheduling algorithm with pre-configured fixed weights for each priority queue. The problem is that the intensity of traffic in general and of each packet class occasionally changes. Therefore, in this work, we suggest using the particle swarm optimization algorithm to find the optimal weights for the weighted fair round-robin algorithm (WFRR) by considering the variable densities of the traffic. This work presents a framework to simulate router operations by determining the weights and schedule packets and forwarding them. The proposed algorithm to optimize the weights is compared with the conventional WFRR algorithm, and the results show that the particle swarm optimization for the weighted round-robin algorithm is more efficient than WFRR, especially in high-intensity traffic. Moreover, the average packet-loss ratio does not exceed 7%, and the proposed algorithms are better than the conventional CBWRR algorithm and the related work results.https://www.mdpi.com/2079-9292/12/2/462computer networksoftware defined networkartificial intelligencePSO algorithm |
| spellingShingle | Rana Fareed Ghani Laith Al-Jobouri Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm Electronics computer network software defined network artificial intelligence PSO algorithm |
| title | Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm |
| title_full | Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm |
| title_fullStr | Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm |
| title_full_unstemmed | Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm |
| title_short | Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm |
| title_sort | packet loss optimization in router forwarding tasks based on the particle swarm algorithm |
| topic | computer network software defined network artificial intelligence PSO algorithm |
| url | https://www.mdpi.com/2079-9292/12/2/462 |
| work_keys_str_mv | AT ranafareedghani packetlossoptimizationinrouterforwardingtasksbasedontheparticleswarmalgorithm AT laithaljobouri packetlossoptimizationinrouterforwardingtasksbasedontheparticleswarmalgorithm |