APWR: Address-Partitioned wildcard routing for flow management in SDN-based datacenter networks

Kuan Tsen Kuo, Cheng Suo, Charles H.P. Wen

Research output: Contribution to conferencePaper

Abstract

Network performance and scalability become major issues in cloud computing. The OpenFlow framework enabling flowlevel management makes routing more effective and simpler in datacenter networks (DCNs). A prior routing algorithm named DENDIST-FM shows a good result in improving throughput and avoiding congestion of DCNs. However, flow migration for cloud management often incurs extra overhead from modifying the flow tables in switches. Therefore, on the basis of DENDISTFM, we propose a novel address-partitioned wildcard routing (APWR) scheme, which leverages the symmetry of a Portland topology and applies wildcard matching to achieve low cost for flow-table modification. Simulation results demonstrate that on a Portland 8-16-16 datacenter network with 128 host machines, the proposed scheme achieves throughput as good as DENDISTFM does, but reduces 70% cost on flow-table modifications used by DENDIST-FM. As a result, our APWR scheme is proven a practical algorithm for improving network performance and reducing flow-migration cost, simultaneously.

Original languageEnglish
Pages70-76
Number of pages7
DOIs
StatePublished - 1 Jan 2014
EventInternational Conference on Software Intelligence Technologies and Applications and International Conference on Frontiers of Internet of Things, 2014 - Hsinchu, Taiwan
Duration: 4 Dec 20146 Dec 2014

Conference

ConferenceInternational Conference on Software Intelligence Technologies and Applications and International Conference on Frontiers of Internet of Things, 2014
CountryTaiwan
CityHsinchu
Period4/12/146/12/14

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    Kuo, K. T., Suo, C., & Wen, C. H. P. (2014). APWR: Address-Partitioned wildcard routing for flow management in SDN-based datacenter networks. 70-76. Paper presented at International Conference on Software Intelligence Technologies and Applications and International Conference on Frontiers of Internet of Things, 2014, Hsinchu, Taiwan. https://doi.org/10.1049/cp.2014.1538