Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads
Segment routing has been a novel architecture for traffic engineering in recent years. However, segment routing brings control overheads, i.e., additional packets headers should be inserted. The overheads can greatly reduce the forwarding efficiency for a large network, when segment headers become t...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2023-03-01
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| Series: | Big Data Mining and Analytics |
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| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2022.9020018 |
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| _version_ | 1832557727549751296 |
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| author | Shu Yang Ruiyu Chen Laizhong Cui Xiaolei Chang |
| author_facet | Shu Yang Ruiyu Chen Laizhong Cui Xiaolei Chang |
| author_sort | Shu Yang |
| collection | DOAJ |
| description | Segment routing has been a novel architecture for traffic engineering in recent years. However, segment routing brings control overheads, i.e., additional packets headers should be inserted. The overheads can greatly reduce the forwarding efficiency for a large network, when segment headers become too long. To achieve the best of two targets, we propose the intelligent routing scheme for traffic engineering (IRTE), which can achieve load balancing with limited control overheads. To achieve optimal performance, we first formulate the problem as a mapping problem that maps different flows to key diversion points. Second, we prove the problem is nondeterministic polynomial (NP)-hard by reducing it to a k-dense subgraph problem. To solve this problem, we develop an ant colony optimization algorithm as improved ant colony optimization (IACO), which is widely used in network optimization problems. We also design the load balancing algorithm with diversion routing (LBA-DR), and analyze its theoretical performance. Finally, we evaluate the IRTE in different real-world topologies, and the results show that the IRTE outperforms traditional algorithms, e.g., the maximum bandwidth is 24.6% lower than that of traditional algorithms when evaluating on BellCanada topology. |
| format | Article |
| id | doaj-art-d00fecf39f3241fcba962ddc627ff14c |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2023-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-d00fecf39f3241fcba962ddc627ff14c2025-02-03T03:00:39ZengTsinghua University PressBig Data Mining and Analytics2096-06542023-03-0161557110.26599/BDMA.2022.9020018Intelligent Segment Routing: Toward Load Balancing with Limited Control OverheadsShu Yang0Ruiyu Chen1Laizhong Cui2Xiaolei Chang3College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518000, ChinaCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518000, ChinaCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518000, ChinaTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518071, ChinaSegment routing has been a novel architecture for traffic engineering in recent years. However, segment routing brings control overheads, i.e., additional packets headers should be inserted. The overheads can greatly reduce the forwarding efficiency for a large network, when segment headers become too long. To achieve the best of two targets, we propose the intelligent routing scheme for traffic engineering (IRTE), which can achieve load balancing with limited control overheads. To achieve optimal performance, we first formulate the problem as a mapping problem that maps different flows to key diversion points. Second, we prove the problem is nondeterministic polynomial (NP)-hard by reducing it to a k-dense subgraph problem. To solve this problem, we develop an ant colony optimization algorithm as improved ant colony optimization (IACO), which is widely used in network optimization problems. We also design the load balancing algorithm with diversion routing (LBA-DR), and analyze its theoretical performance. Finally, we evaluate the IRTE in different real-world topologies, and the results show that the IRTE outperforms traditional algorithms, e.g., the maximum bandwidth is 24.6% lower than that of traditional algorithms when evaluating on BellCanada topology.https://www.sciopen.com/article/10.26599/BDMA.2022.9020018traffic engineeringsegment routingbandwidth load balancingant colony optimization |
| spellingShingle | Shu Yang Ruiyu Chen Laizhong Cui Xiaolei Chang Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads Big Data Mining and Analytics traffic engineering segment routing bandwidth load balancing ant colony optimization |
| title | Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads |
| title_full | Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads |
| title_fullStr | Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads |
| title_full_unstemmed | Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads |
| title_short | Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads |
| title_sort | intelligent segment routing toward load balancing with limited control overheads |
| topic | traffic engineering segment routing bandwidth load balancing ant colony optimization |
| url | https://www.sciopen.com/article/10.26599/BDMA.2022.9020018 |
| work_keys_str_mv | AT shuyang intelligentsegmentroutingtowardloadbalancingwithlimitedcontroloverheads AT ruiyuchen intelligentsegmentroutingtowardloadbalancingwithlimitedcontroloverheads AT laizhongcui intelligentsegmentroutingtowardloadbalancingwithlimitedcontroloverheads AT xiaoleichang intelligentsegmentroutingtowardloadbalancingwithlimitedcontroloverheads |