Dynamic Link Metric Selection for Traffic Aggregation and Multipath Transmission in Software-Defined Networks
Source abstract
Abstract
Software-defined networks (SDNs) are expanding their presence beyond laboratories, campus networks, ISPs, and data centre networks, moving into various domains. Although originally designed for campus networks, SDNs face scalability challenges, especially with the use of OpenFlow. Addressing these challenges requires innovative traffic management mechanisms to efficiently handle the growing number of connected devices and the increasing volume of traffic from various types of applications. This article proposes an innovative method for link weight selection that incorporates multipath transmission and flow aggregation in the SDNs. This novel approach improves resource utilization in two key ways. First, it involves the preservation of bandwidth during congestion. Second, it minimizes internal resource usage, as illustrated by a reduction in the number of table entries in switches. Resources undergo optimization through the introduction of a novel mechanism for flow aggregation. This novel mechanism, coupled with multipath transmission, enables adaptive responses to dynamic changes in network conditions. The aggregation process leads to a reduced number of flow entries in the core switches compared to the conventional operation of OpenFlow. The proposed scenarios for link weight allocation allow for a reduction in the number of entries in the core switches by up to 99%. The application of the proposed method also results in an increase of 58% in traffic transmission.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Software-Defined Networks and 5G · Advanced Optical Network Technologies · Radiation Effects in Electronics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
AGH University of Krakow, Institute of Telecommunications, Al. Mickiewicza 30, 30-059 Kraków, Poland
Institute of Applied Computer Science, Mark Kac Center for Complex Systems Research, Jagiellonian University, Łojasiewicza 11, 30-348 Kraków, Poland
Funding
AGH University of Krakow · Polish Ministry of Science and Higher Education · Jagiellonian University · Polish Innovation Economy Operational Program · National Research Institute
References (32)
Show source-provided references
1. Optimizing OSPF/IS-IS weights in a changing world10.1109/JSAC.2002.1003042 ↗
2. A survey on methods to provide multipath transmission in wired packet networks10.1016/j.comnet.2014.12.001 ↗
3. Multipath Transmission for the Internet: A Survey10.1109/COMST.2016.2586112 ↗
4. Survey on Software-Defined Networking10.1109/COMST.2014.2330903 ↗
5. Chuang, C.C., Yu, Y.J., Pang, A.C., and Chen, G.Y. (2016, January 4–8). Minimization of TCAM Usage for SDN Scalability in Wireless Data Centers. Proceedings of the 2016 IEEE Global Communications Conference (GLOBECOM), Washington, DC, USA.10.1109/GLOCOM.2016.7841984 ↗
6. DevoFlow: Scaling Flow Management for High-Performance Networks10.1145/2043164.2018466 ↗
7. On scalability of software-defined networking10.1109/MCOM.2013.6461198 ↗
8. MPLS-based reduction of flow table entries in SDN switches supporting multipath transmission10.1016/j.comcom.2019.12.052 ↗
9. The Open Networking Foundation (2015). OpenFlow Switch Specification v1.5.1, The Open Networking Foundation.
10. Pióro, M., and Medhi, D. (2004). Routing, Flow, and Capacity Design in Communication and Computer Networks, Morgan Kaufmann Publishers Inc.10.1016/B978-012557189-0/50011-1 ↗
11. The ns-3 Consortium (2024, June 17). The ns-3 Network Simulator. Available online: https://www.nsnam.org/.
12. SNDlib 1.0—Survivable Network Design Library
13. Mimidis, A., Caba, C., and Soler, J. (2016, January 6–10). Dynamic Aggregation of Traffic Flows in SDN: Applied to Backhaul Networks. Proceedings of the 2016 IEEE NetSoft Conference and Workshops (NetSoft), Seoul, Republic of Korea.10.1109/NETSOFT.2016.7502459 ↗
14. Delayed Installation and Expedited Eviction: An Alternative Approach to Reduce Flow Table Occupancy in SDN Switches10.1109/TNET.2018.2841397 ↗
15. Flows Reduction Scheme Using Two MPLS Tags in Software-Defined Network10.1109/ACCESS.2017.2725139 ↗
16. Flow aggregation for large-scale SDNs with scattered address space allocation10.1016/j.jnca.2020.102787 ↗
17. Jiawei, W., Xiuquan, Q., and HuiJuan, L. (2022, January 27–30). Dynamic Multipath Routing Mechanism for Multimedia Data Flow Scheduling Over Software Defined Networks. Proceedings of the 2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), Baltimore, MD, USA.10.1109/DSN-W54100.2022.00040 ↗
18. Scalable Rate Allocation for SDN With Diverse Service Requirements10.1109/TSC.2020.3043595 ↗
19. B4: Experience with a Globally-deployed Software Defined WAN10.1145/2534169.2486019 ↗
20. Gredler, H., Medved, J., Previdi, S., Farrel, A., and Ray, S. (2016). North-Bound Distribution of Link-State and Traffic Engineering (TE) Information Using BGP, Internet Engineering Task Force (IETF). IETF RFC 7752.10.17487/RFC7752 ↗
21. A Survey on the Path Computation Element (PCE) Architecture10.1109/SURV.2013.011413.00087 ↗
22. Crabbe, E., Minei, I., Medved, J., and Varga, R. (2017). Path Computation Element Communication Protocol (PCEP) Extensions for Stateful PCE, Internet Engineering Task Force (IETF). IETF RFC 8231.10.17487/RFC8231 ↗
23. Rzym, G., Wajda, K., and Rzym, K. (2016, January 10–14). Analysis of PCE-based path optimization in multi-domain SDN/MPLS/BGP-LS network. Proceedings of the 2016 18th International Conference on Transparent Optical Networks (ICTON), Trento, Italy.10.1109/ICTON.2016.7550505 ↗
24. Wang, Y.C., Lin, Y.D., and Chang, G.Y. (2017, January 12–14). SDN-based Dynamic Multipath Forwarding for Inter-data Center Networking. Proceedings of the 2017 IEEE International Symposium on Local and Metropolitan Area Networks LANMAN, Osaka, Japan.
25. Lin, W., Niu, Y., Zhang, X., Wei, L., and Zhang, C. (2016, January 23–25). Using Path Label Routing in Wide Area Software-Defined Networks with OpenFlow. Proceedings of the 2016 International Conference on Networking and Network Applications NaNA, Hakodate City, Japan.10.1109/NaNA.2016.40 ↗
26. FlowStat: Adaptive Flow-Rule Placement for Per-Flow Statistics in SDN10.1109/JSAC.2019.2894239 ↗
27. On SDN-Driven Network Optimization and QoS Aware Routing Using Multiple Paths10.1109/TWC.2020.2986408 ↗
28. Shu, Y., and Gao, D. (2023, January 17–18). A Dynamic Multipath Load Balancing Algorithm Based on Particle Swarm Optimization in DCN. Proceedings of the 2023 IEEE 14th International Conference on Software Engineering and Service Science (ICSESS), Beijing, China.10.1109/ICSESS58500.2023.10293042 ↗
29. A comprehensive survey of load balancing techniques in software-defined network10.1016/j.jnca.2020.102856 ↗
30. Barakabitze, A.A., Sun, L., Mkwawa, I.H., and Ifeachor, E. (2018, January 20–24). A Novel QoE-Centric SDN-Based Multipath Routing Approach for Multimedia Services over 5G Networks. Proceedings of the 2018 IEEE International Conference on Communications (ICC), Kansas City, MO, USA.10.1109/ICC.2018.8422617 ↗
31. TeaVisor: Network Hypervisor for Bandwidth Isolation in SDN-NV10.1109/TCC.2022.3225915 ↗
32. Reinforcement Learning-Based Service-Oriented Dynamic Multipath Routing in SDN10.1155/2022/1330993 ↗