A Novel Strategy for Computing Routing Paths for Software-Defined Networks Based on MOCell Optimization
Software-defined networking (SDN) is the fastest growing and most widely deployed network infrastructure due to its adaptability to new networking technologies and intelligent applications. SDN simplifies network management and control by separating the control plane from the data plane. The SDN con...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/22/11590 |
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| author | Jose E. Gonzalez-Trejo Raul Rivera-Rodriguez Andrei Tchernykh Jose E. Lozano-Rizk Salvador Villarreal-Reyes Alejandro Galaviz-Mosqueda Jose L. Gonzalez Compean |
| author_facet | Jose E. Gonzalez-Trejo Raul Rivera-Rodriguez Andrei Tchernykh Jose E. Lozano-Rizk Salvador Villarreal-Reyes Alejandro Galaviz-Mosqueda Jose L. Gonzalez Compean |
| author_sort | Jose E. Gonzalez-Trejo |
| collection | DOAJ |
| description | Software-defined networking (SDN) is the fastest growing and most widely deployed network infrastructure due to its adaptability to new networking technologies and intelligent applications. SDN simplifies network management and control by separating the control plane from the data plane. The SDN controller performs the routing process using the traditional shortest path approach to obtain end-to-end paths. This process usually does not consider the nodes’ capacity and may cause network congestion and delays, affecting flow performance. Therefore, we evaluate the most conventional routing criteria in the SDN scenario based on Dijkstra’s algorithm and compare the found paths with our proposal based on a cellular genetic algorithm for multi-objective optimization (MOCell). We compare our proposal with another multi-objective evolutionary algorithm based on decomposition (MOEA/D) for benchmark purposes. We evaluate various network parameters such as bandwidth, delay, and packet loss to find the optimal end-to-end path. We consider a large-scale inter-domain SDN scenario. The simulation results show that our proposed method can improve the performance of data streams with TCP traffic by up to 54% over the traditional routing method of the shortest path and by 33% for the highest bandwidth path. When transmitting a constant data stream using the UDP protocol, the throughput of the MOCell method is more than 1.65% and 9.77% for the respective paths. |
| first_indexed | 2024-03-09T18:29:07Z |
| format | Article |
| id | doaj.art-30eb91a4da4240558124ce417f94de01 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T18:29:07Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-30eb91a4da4240558124ce417f94de012023-11-24T07:37:41ZengMDPI AGApplied Sciences2076-34172022-11-0112221159010.3390/app122211590A Novel Strategy for Computing Routing Paths for Software-Defined Networks Based on MOCell OptimizationJose E. Gonzalez-Trejo0Raul Rivera-Rodriguez1Andrei Tchernykh2Jose E. Lozano-Rizk3Salvador Villarreal-Reyes4Alejandro Galaviz-Mosqueda5Jose L. Gonzalez Compean6Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Electronics and Telecommunications Department, Ensenada 22860, MexicoCentro de Investigacion Cientifica y de Educacion Superior de Ensenada, Telematics Division, Ensenada 22860, MexicoCentro de Investigacion Cientifica y de Educacion Superior de Ensenada, Computer Science Department, Ensenada 22860, MexicoCentro de Investigacion Cientifica y de Educacion Superior de Ensenada, Telematics Division, Ensenada 22860, MexicoCentro de Investigacion Cientifica y de Educacion Superior de Ensenada, Electronics and Telecommunications Department, Ensenada 22860, MexicoMonterrey Unit, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Apocada 66629, MexicoCentro de Investigación y de Estudios Avanzados del I.P.N. (Cinvestav Tamaulipas), Victoria City 87130, MexicoSoftware-defined networking (SDN) is the fastest growing and most widely deployed network infrastructure due to its adaptability to new networking technologies and intelligent applications. SDN simplifies network management and control by separating the control plane from the data plane. The SDN controller performs the routing process using the traditional shortest path approach to obtain end-to-end paths. This process usually does not consider the nodes’ capacity and may cause network congestion and delays, affecting flow performance. Therefore, we evaluate the most conventional routing criteria in the SDN scenario based on Dijkstra’s algorithm and compare the found paths with our proposal based on a cellular genetic algorithm for multi-objective optimization (MOCell). We compare our proposal with another multi-objective evolutionary algorithm based on decomposition (MOEA/D) for benchmark purposes. We evaluate various network parameters such as bandwidth, delay, and packet loss to find the optimal end-to-end path. We consider a large-scale inter-domain SDN scenario. The simulation results show that our proposed method can improve the performance of data streams with TCP traffic by up to 54% over the traditional routing method of the shortest path and by 33% for the highest bandwidth path. When transmitting a constant data stream using the UDP protocol, the throughput of the MOCell method is more than 1.65% and 9.77% for the respective paths.https://www.mdpi.com/2076-3417/12/22/11590quality of serviceroutingsoftware-defined networkgenetic algorithms |
| spellingShingle | Jose E. Gonzalez-Trejo Raul Rivera-Rodriguez Andrei Tchernykh Jose E. Lozano-Rizk Salvador Villarreal-Reyes Alejandro Galaviz-Mosqueda Jose L. Gonzalez Compean A Novel Strategy for Computing Routing Paths for Software-Defined Networks Based on MOCell Optimization Applied Sciences quality of service routing software-defined network genetic algorithms |
| title | A Novel Strategy for Computing Routing Paths for Software-Defined Networks Based on MOCell Optimization |
| title_full | A Novel Strategy for Computing Routing Paths for Software-Defined Networks Based on MOCell Optimization |
| title_fullStr | A Novel Strategy for Computing Routing Paths for Software-Defined Networks Based on MOCell Optimization |
| title_full_unstemmed | A Novel Strategy for Computing Routing Paths for Software-Defined Networks Based on MOCell Optimization |
| title_short | A Novel Strategy for Computing Routing Paths for Software-Defined Networks Based on MOCell Optimization |
| title_sort | novel strategy for computing routing paths for software defined networks based on mocell optimization |
| topic | quality of service routing software-defined network genetic algorithms |
| url | https://www.mdpi.com/2076-3417/12/22/11590 |
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