Reducing and Balancing Flow Table Entries in Software-Defined Networks

Xuya Jia; Yong Jiang; Zehua Guo; Zhenwei Wu

doi:10.1109/LCN.2016.96

Reducing and Balancing Flow Table Entries in Software-Defined Networks

Xuya Jia
, Yong Jiang
, Zehua Guo
, Zhenwei Wu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

23 Scopus citations

Abstract

Software-Defined Networking (SDN) allows flexible and efficient management of networks. However, the limited capacity of flow tables in SDN switches hinders the deployment of SDN. In this paper, we propose a novel routing scheme to improve the efficiency of flow tables in SDNs. To efficiently use the routing scheme, we formulate an optimization problem with the objective to maximize the number of flows in the network, constrained by the limited flow table space in SDN switches. The problem is NP-hard, and we propose the K Similar Greedy Tree (KSGT) algorithm to solve it. We evaluate the performance of KSGT against 'traditional' SDN solutions with real-world topologies and traffic. The results show that, compared to the existing solutions, KSGT can reduce about 60% of flow entries when processing the same amount of flows, and improve about 25% of the successful installation and forwarding flows under the same flow table space.

Original language	English (US)
Title of host publication	Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016
Publisher	IEEE Computer Society
Pages	575-578
Number of pages	4
ISBN (Electronic)	9781509020546
DOIs	https://doi.org/10.1109/LCN.2016.96
State	Published - Dec 22 2016
Externally published	Yes
Event	41st IEEE Conference on Local Computer Networks, LCN 2016 - Dubai, United Arab Emirates Duration: Nov 7 2016 → Nov 10 2016

Publication series

Name	Proceedings - Conference on Local Computer Networks, LCN

Other

Other	41st IEEE Conference on Local Computer Networks, LCN 2016
Country/Territory	United Arab Emirates
City	Dubai
Period	11/7/16 → 11/10/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Flow table reuse
MPLS
Overhead
Software-Defined Networking

Publisher link

10.1109/LCN.2016.96

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Reducing and Balancing Flow Table Entries in Software-Defined Networks. / Jia, Xuya; Jiang, Yong; Guo, Zehua et al.
Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016. IEEE Computer Society, 2016. p. 575-578 7796844 (Proceedings - Conference on Local Computer Networks, LCN).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jia, X, Jiang, Y, Guo, Z & Wu, Z 2016, Reducing and Balancing Flow Table Entries in Software-Defined Networks. in Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016., 7796844, Proceedings - Conference on Local Computer Networks, LCN, IEEE Computer Society, pp. 575-578, 41st IEEE Conference on Local Computer Networks, LCN 2016, Dubai, United Arab Emirates, 11/7/16. https://doi.org/10.1109/LCN.2016.96

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abstract = "Software-Defined Networking (SDN) allows flexible and efficient management of networks. However, the limited capacity of flow tables in SDN switches hinders the deployment of SDN. In this paper, we propose a novel routing scheme to improve the efficiency of flow tables in SDNs. To efficiently use the routing scheme, we formulate an optimization problem with the objective to maximize the number of flows in the network, constrained by the limited flow table space in SDN switches. The problem is NP-hard, and we propose the K Similar Greedy Tree (KSGT) algorithm to solve it. We evaluate the performance of KSGT against 'traditional' SDN solutions with real-world topologies and traffic. The results show that, compared to the existing solutions, KSGT can reduce about 60\% of flow entries when processing the same amount of flows, and improve about 25\% of the successful installation and forwarding flows under the same flow table space.",

keywords = "Flow table reuse, MPLS, Overhead, Software-Defined Networking",

author = "Xuya Jia and Yong Jiang and Zehua Guo and Zhenwei Wu",

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doi = "10.1109/LCN.2016.96",

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Y1 - 2016/12/22

N2 - Software-Defined Networking (SDN) allows flexible and efficient management of networks. However, the limited capacity of flow tables in SDN switches hinders the deployment of SDN. In this paper, we propose a novel routing scheme to improve the efficiency of flow tables in SDNs. To efficiently use the routing scheme, we formulate an optimization problem with the objective to maximize the number of flows in the network, constrained by the limited flow table space in SDN switches. The problem is NP-hard, and we propose the K Similar Greedy Tree (KSGT) algorithm to solve it. We evaluate the performance of KSGT against 'traditional' SDN solutions with real-world topologies and traffic. The results show that, compared to the existing solutions, KSGT can reduce about 60% of flow entries when processing the same amount of flows, and improve about 25% of the successful installation and forwarding flows under the same flow table space.

AB - Software-Defined Networking (SDN) allows flexible and efficient management of networks. However, the limited capacity of flow tables in SDN switches hinders the deployment of SDN. In this paper, we propose a novel routing scheme to improve the efficiency of flow tables in SDNs. To efficiently use the routing scheme, we formulate an optimization problem with the objective to maximize the number of flows in the network, constrained by the limited flow table space in SDN switches. The problem is NP-hard, and we propose the K Similar Greedy Tree (KSGT) algorithm to solve it. We evaluate the performance of KSGT against 'traditional' SDN solutions with real-world topologies and traffic. The results show that, compared to the existing solutions, KSGT can reduce about 60% of flow entries when processing the same amount of flows, and improve about 25% of the successful installation and forwarding flows under the same flow table space.

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KW - MPLS

KW - Overhead

KW - Software-Defined Networking

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ER -

Reducing and Balancing Flow Table Entries in Software-Defined Networks

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