SFCMon: An Efficient and Scalable Monitoring System for Network Flows in SFC-enabled Domains
Abstract
A comprehensive monitoring system is essential to assist solutions for most of SFC problems. Therefore, in this work, we propose SFCMon, an efficient and scalable monitoring solution to keep track network flows in SFC environments. To achieve the desired goals, SFCMon works with a pipeline of probabilistic data structures to detect and store large flows as well as perflow counters. For evaluation purposes, based on the SFC reference architecture defined by RFC 7665, we implement a Proof-of-Concept (PoC) framework, which provides a P4-based SFC switch and Python-based SFC Controller. Presented initial experiments demonstrate that SFCMon introduces a negligible performance penalty while providing significant scalability gains.
Keywords:
Network function virtualization, service function chaining, bloom filter, invertible bloom lookup table, count-min sketch, programmable data plane, p4.
References
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Cormode, G. and Muthukrishnan, S. (2005). An improved data stream summary: the count-min sketch and its applications. Journal ofAlgorithms, 55(1):58 – 75.
Estan, C. and Varghese, G. (2003). New directions in traffic measurement and accounting: Focusing on the elephants, ignoring the mice. ACM Trans. Comput. Syst., 21(3):270– 313.
ETSI (2015). Network functions virtualisation (nfv) - network operator perspectives on industry progress. White Paper.
Goodrich, M. T. and Mitzenmacher, M. (2011). Invertible bloom lookup tables. In 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Aller- ton), pages 792–799.
Grandi, F. (2018). On the analysis of bloom filters. Information Processing Letters, 129:35 – 39.
Halpern, J. M. and Pignataro, C. (2015). Service Function Chaining (SFC) Architecture. RFC 7665.
Li, Y., Miao, R., Kim, C., and Yu, M. (2016). Flowradar: A better netflow for data centers. In 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 16), pages 311–324, Santa Clara, CA. USENIX Association.
Liu, Z., Manousis, A., Vorsanger, G., Sekar, V., and Braverman, V. (2016). One sketch to rule them all: Rethinking network flow monitoring with univmon. In Proceedings of the 2016 ACM SIGCOMM Conference, SIGCOMM ’16, pages 101–114, New York, NY, USA. ACM.
Medhat, A. M., Taleb, T., Elmangoush, A., Carella, G. A., Covaci, S., and Magedanz, T. (2017). Service function chaining in next generation networks: State of the art and research challenges. IEEE Communications Magazine, 55(2):216–223.
Mori, T., Uchida, M., Kawahara, R., Pan, J., and Goto, S. (2004). Identifying elephant flows through periodically sampled packets. In Proceedings of the 4th ACM SIG- COMM Conference on Internet Measurement, IMC ’04, pages 115–120, New York, NY, USA. ACM.
Patgiri, R., Nayak, S., and Borgohain, S. K. (2018). Preventing ddos using bloom filter: A survey. CoRR, abs/1810.06689.
Pereira, F., Neves, N., and Ramos, F. M. V. (2017). Secure network monitoring using pro- grammable data planes. In 2017 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), pages 286–291.
Quinn, P., Elzur, U., and Pignataro, C. (2018). Network Service Header (NSH). RFC 8300.
Roughgarden, T. and Valiant, G. (2015). Approximate Heavy Hitters and the Count- Min Sketch. http://theory.stanford.edu/˜tim/s15/l/l2.pdf. On- line; accessed 01 April 2019.
Shirali-Shahreza, S. and Ganjali, Y. (2015). Rewiflow: Restricted wildcard openflow rules. SIGCOMM Comput. Commun. Rev., 45(5):29–35.
Sivaraman, V., Narayana, S., Rottenstreich, O., Muthukrishnan, S., and Rexford, J. (2017). Heavy-hitter detection entirely in the data plane. In Proceedings of the Sym- posium on SDN Research, SOSR ’17, pages 164–176, New York, NY, USA. ACM.
Yang, T., Jiang, J., Liu, P., Huang, Q., Gong, J., Zhou, Y., Miao, R., Li, X., and Uhlig, S. (2018). Elastic sketch: Adaptive and fast network-wide measurements. In Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication, SIGCOMM ’18, pages 561–575, New York, NY, USA. ACM.
Zhou, D., Yan, Z., Fu, Y., and Yao, Z. (2018). A survey on network data collection. Journal ofNetwork and Computer Applications, 116:9 – 23.
Bhamare, D., Jain, R., Samaka, M., and Erbad, A. (2016). A survey on service function chaining. Journal ofNetwork and Computer Applications, 75:138 – 155.
Bloom, B. H. (1970). Space/time trade-offs in hash coding with allowable errors. Com- mun. ACM, 13(7):422–426.
Bosshart, P., Daly, D., Gibb, G., Izzard, M., McKeown, N., Rexford, J., Schlesinger, C., Talayco, D., Vahdat, A., Varghese, G., and Walker, D. (2014). P4: Program- ming protocol-independent packet processors. SIGCOMM Comput. Commun. Rev., 44(3):87–95.
Boucadair, M. (2016). Service Function Chaining (SFC) Control Plane Components & Requirements. Internet-Draft draft-ietf-sfc-control-plane-08, Internet Engineering Task Force. Work in Progress.
Broder, A., Mitzenmacher, M., and Mitzenmacher, A. B. I. M. (2002). Network applica- tions of bloom filters: A survey. In Internet Mathematics, pages 636–646.
Cormode, G. and Muthukrishnan, S. (2005). An improved data stream summary: the count-min sketch and its applications. Journal ofAlgorithms, 55(1):58 – 75.
Estan, C. and Varghese, G. (2003). New directions in traffic measurement and accounting: Focusing on the elephants, ignoring the mice. ACM Trans. Comput. Syst., 21(3):270– 313.
ETSI (2015). Network functions virtualisation (nfv) - network operator perspectives on industry progress. White Paper.
Goodrich, M. T. and Mitzenmacher, M. (2011). Invertible bloom lookup tables. In 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Aller- ton), pages 792–799.
Grandi, F. (2018). On the analysis of bloom filters. Information Processing Letters, 129:35 – 39.
Halpern, J. M. and Pignataro, C. (2015). Service Function Chaining (SFC) Architecture. RFC 7665.
Li, Y., Miao, R., Kim, C., and Yu, M. (2016). Flowradar: A better netflow for data centers. In 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 16), pages 311–324, Santa Clara, CA. USENIX Association.
Liu, Z., Manousis, A., Vorsanger, G., Sekar, V., and Braverman, V. (2016). One sketch to rule them all: Rethinking network flow monitoring with univmon. In Proceedings of the 2016 ACM SIGCOMM Conference, SIGCOMM ’16, pages 101–114, New York, NY, USA. ACM.
Medhat, A. M., Taleb, T., Elmangoush, A., Carella, G. A., Covaci, S., and Magedanz, T. (2017). Service function chaining in next generation networks: State of the art and research challenges. IEEE Communications Magazine, 55(2):216–223.
Mori, T., Uchida, M., Kawahara, R., Pan, J., and Goto, S. (2004). Identifying elephant flows through periodically sampled packets. In Proceedings of the 4th ACM SIG- COMM Conference on Internet Measurement, IMC ’04, pages 115–120, New York, NY, USA. ACM.
Patgiri, R., Nayak, S., and Borgohain, S. K. (2018). Preventing ddos using bloom filter: A survey. CoRR, abs/1810.06689.
Pereira, F., Neves, N., and Ramos, F. M. V. (2017). Secure network monitoring using pro- grammable data planes. In 2017 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), pages 286–291.
Quinn, P., Elzur, U., and Pignataro, C. (2018). Network Service Header (NSH). RFC 8300.
Roughgarden, T. and Valiant, G. (2015). Approximate Heavy Hitters and the Count- Min Sketch. http://theory.stanford.edu/˜tim/s15/l/l2.pdf. On- line; accessed 01 April 2019.
Shirali-Shahreza, S. and Ganjali, Y. (2015). Rewiflow: Restricted wildcard openflow rules. SIGCOMM Comput. Commun. Rev., 45(5):29–35.
Sivaraman, V., Narayana, S., Rottenstreich, O., Muthukrishnan, S., and Rexford, J. (2017). Heavy-hitter detection entirely in the data plane. In Proceedings of the Sym- posium on SDN Research, SOSR ’17, pages 164–176, New York, NY, USA. ACM.
Yang, T., Jiang, J., Liu, P., Huang, Q., Gong, J., Zhou, Y., Miao, R., Li, X., and Uhlig, S. (2018). Elastic sketch: Adaptive and fast network-wide measurements. In Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication, SIGCOMM ’18, pages 561–575, New York, NY, USA. ACM.
Zhou, D., Yan, Z., Fu, Y., and Yao, Z. (2018). A survey on network data collection. Journal ofNetwork and Computer Applications, 116:9 – 23.
Published
2019-07-11
How to Cite
BONFIM, Michel; DIAS, Kelvin ; FERNANDES , Stenio .
SFCMon: An Efficient and Scalable Monitoring System for Network Flows in SFC-enabled Domains. In: PRE-IETF WORKSHOP (WPIETF), 6. , 2019, Belém.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
ISSN 2595-6388.
DOI: https://doi.org/10.5753/wpietf.2019.6581.
