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Proactive eviction of flow entry for SDN based on hidden Markov model

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Abstract

With the fast development of software defined network (SDN), numerous researches have been conducted for maximizing the performance of SDN. Currently, flow tables are utilized in OpenFlows witch for routing. Due to the space limitation of flow table and switch capacity, various issues exist in dealing with the flows. The existing schemes typically employ reactive approach such that the selection of evicted entries occurs when timeout or table miss occurs. In this paper a proactive approach is proposed based on the prediction of the probability of matching of the entries. Here eviction occurs proactively when the utilization of flow table exceeds a threshold, and the flow entry of the lowest matching probability is evicted. The matching probability is estimated using hidden Markov model (HMM). Computersimulation reveals that it significantly enhances the prediction accuracy and decreases the number of table misses compared to the standard Hard timeout scheme and Flow master scheme.

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Acknowledgements

This work was partly supported by the Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (2016-0-00133, Research on Edge computing via collective intelligence of hyper connection IoT nodes), Korea, under the National Program for Excellence in SW supervised by the IITP (Institute for Information & communications Technology Promotion) (2015-0-00914), Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2016R1A6A3A11931385, Research of key technologies based on software defined wireless sensor network for realtime public safety service, 2017R1A2B2009095, Research on SDN-based WSN Supporting Real-time Stream Data Processing and Multiconnectivity), the second Brain Korea 21 PLUS project.

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Authors and Affiliations

  1. College of Software, Sungkyunkwan University, Suwon, 440746, Korea

    Gan Huang & Hee Yong Youn

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  1. Gan Huang
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  2. Hee Yong Youn
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Correspondence to Hee Yong Youn.

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Gan Huang received the BS in Electronic and Information Engineering from Chuzhou Univerisity, China in 2012, and the MS from in Computer Science from Anhui Polytechnic University, China in 2016. Currently, he is a PhD Student at College of Information & Communication Engineering, Sungkyunkwan University Korea, Korea. His research interests include SDN (software defined networking), Ubiquitous, and Distributed computing.

Hee Yong Youn received the BS and MS in electrical engineering from Seoul National University, Korea in 1977 and 1979, respectively, and the PhD in computer engineering from the University of Massachusetts at Amherst, USA in 1988. He had been Associate Professor of Department of Computer Science and Engineering, The University of Texas at Arlington, USA until 1999. He is Professor of College of Information and Communication Engineering and Director of Ubiquitous Computing Technology Research Institute, Sungkyunkwan University, Korea, and he is presently visiting SW R&D Center, Device Solutions, and Samsung Electronics. His research interests include cloud and ubiquitous computing, system software and middleware, and RFID/USN. He has published numerous papers and received Outstanding Paper Award from the 1988 IEEE International Conference on Distributed Computing Systems, 1992 Supercomputing, IEEE 2012 Int’l Conference on Computer, Information and Telecommunication Systems, and CyberC 2014. Prof. Youn has been General Co-Chair of IEEE PRDC 2001, Int’l Conf. on Ubiquitous Computing Systems (UCS) in 2006 and 2009, UbiComp 2008, CyberC 2010, Program Chair of PDCS 2003 and UCS 2007, respectively.

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Huang, G., Youn, H.Y. Proactive eviction of flow entry for SDN based on hidden Markov model. Front. Comput. Sci. 14, 144502 (2020). https://doi.org/10.1007/s11704-018-8048-2

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  • DOI: https://doi.org/10.1007/s11704-018-8048-2

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