Um Modelo Formal de Propósito Geral para Simulações de Redes Definidas por Software
Resumo
Redes Definidas por Software (SDN) permitem uma maior flexibilidade na gerência de fluxos de rede devido a clara separação entre o plano de controle e o plano de dados. Nesse contexto, mensurar as características que afetam, por exemplo, o desempenho da rede é uma tarefa árdua diante de diferentes cenários, requisitos e objetivos distintos de otimização. Assim, desenvolvemos um modelo baseado no formalismo de especificação de sistemas a eventos discretos (DEVS) para que seja possível simular cenários de rede SDN de forma flexível e rápida a fim de auxiliar no entendimento do funcionamento da rede e de aspectos que podem impactar no seu desempenho. Além disso, é possível ainda avaliar estratégias de otimização que podem ser integradas ao DEVS abrindo a oportunidade para validar diversos outros trabalhos.
Referências
Networkx python package website. https://networkx.lanl.gov/wiki. Accessado: 2016-01-14.
Bari, M. F., Roy, A. R., Chowdhury, S. R., Zhang, Q., Zhani, M. F., Ahmed, R., and Boutaba, R. (2013). Dynamic controller provisioning in software defined networks. In Network and Service Management (CNSM), 2013 9th International Conference on, pages 18–25. IEEE.
Bhuvan, V., Basil, A., Veryx, T., Mark, T., Hewlett-Packard, Manral, V., Sec, N., Banks, S., and Monitoring, V. (2016a). Benchmarking methodology for sdn controller performance draft-ietf-bmwg-sdn-controller-benchmark-meth-01. https://tools.ietf.org/html/draft-ietf-bmwg-sdn-controller-benchmark-meth-01.
Bhuvan, V., Basil, A., Veryx, T., Mark, T., Hewlett-Packard, Manral, V., Sec, N., Banks, S., and Monitoring, V. (2016b). Terminology for benchmarking sdn controller performance draft-ietf-bmwg-sdn-controller-benchmark-term-01. https://tools.ietf.org/html/draft-ietf-bmwg-sdn-controller-benchmark-term-01.
Curtis, A. R., Mogul, J. C., Tourrilhes, J., Yalagandula, P., Sharma, P., and Banerjee, S. (2011). Devoflow: scaling flow management for high-performance networks. In ACM SIGCOMM Computer Communication Review, volume 41, pages 254–265. ACM.
Feamster, N., Rexford, J., and Zegura, E. (2013). The road to sdn. Queue, 11(12):20.
Fishwick, P. A. (1995). Simulation Model Design and Execution: Building Digital Worlds. Prentice Hall PTR, Upper Saddle River, NJ, USA, 1st edition.
Gupta, M., Sommers, J., and Barford, P. (2013). Fast, accurate simulation for sdn prototyping. In Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking, pages 31–36. ACM.
Handigol, N., Heller, B., Jeyakumar, V., Lantz, B., and McKeown, N. (2012). Reproducible network experiments using container-based emulation. In Proceedings of the 8th international conference on Emerging networking experiments and technologies, pages 253–264. ACM.
McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., Shenker, S., and Turner, J. (2008). Openflow: Enabling innovation in campus networks. SIGCOMM Comput. Commun. Rev., 38(2):69–74.
Mello, B. A. and Wainer, G. A. (2016). Scheduling predictability in i-devs by schedulability analysis. Spring Simulation Multi-Conference / Symposium on Theory of Modeling and Simulation (TMS/DEVS), pages 622–629. SCS/ACM.
Molloy, M. K. (1982). Performance analysis using stochastic petri nets. Computers, IEEE Transactions on, 100(9):913–917.
Murata, T. (1989). Petri nets: Properties, analysis and applications. Proceedings of the IEEE, 77(4):541–580.
Puterman, M. L. (2014). Markov decision processes: discrete stochastic dynamic programming. John Wiley & Sons.
R. Gu, E., Li, C., and Wang, R. (2016). Problem statement of sdn and nfv codeployment in cloud datacenters draft-gu-sdnrg-problem-statement-of-sdn-nfv-in-dc-01. https://tools.ietf.org/html/draft-gu-sdnrg-problem-statement-of-sdn-nfv-in-dc-01.
Rexford, J. and Dovrolis, C. (2010). Future internet architecture: Clean-slate versus evolutionary research. Commun. ACM, 53(9):36–40.
Schult, D. A. and Swart, P. (2008). Exploring network structure, dynamics, and function using networkx. In Proceedings of the 7th Python in Science Conferences (SciPy 2008), volume 2008, pages 11–16.
Valmari, A. (1998). The state explosion problem. In Lectures on Petri nets I: Basic models, pages 429–528. Springer.
Wainer, G. (2002). Cd++: a toolkit to develop devs models. Software: Practice and Experience, 32(13):1261–1306.
Wainer, G. A. (2009). Discrete-event modeling and simulation: a practitioner’s approach. CRC Press.
Yu, M., Rexford, J., Freedman, M. J., and Wang, J. (2011). Scalable flow-based networking with difane. ACM SIGCOMM Computer Communication Review, 41(4):351–362.
Zeigler, B. P., Praehofer, H., and Kim, T. G. (2000). Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems. Academic press.
Bari, M. F., Roy, A. R., Chowdhury, S. R., Zhang, Q., Zhani, M. F., Ahmed, R., and Boutaba, R. (2013). Dynamic controller provisioning in software defined networks. In Network and Service Management (CNSM), 2013 9th International Conference on, pages 18–25. IEEE.
Bhuvan, V., Basil, A., Veryx, T., Mark, T., Hewlett-Packard, Manral, V., Sec, N., Banks, S., and Monitoring, V. (2016a). Benchmarking methodology for sdn controller performance draft-ietf-bmwg-sdn-controller-benchmark-meth-01. https://tools.ietf.org/html/draft-ietf-bmwg-sdn-controller-benchmark-meth-01.
Bhuvan, V., Basil, A., Veryx, T., Mark, T., Hewlett-Packard, Manral, V., Sec, N., Banks, S., and Monitoring, V. (2016b). Terminology for benchmarking sdn controller performance draft-ietf-bmwg-sdn-controller-benchmark-term-01. https://tools.ietf.org/html/draft-ietf-bmwg-sdn-controller-benchmark-term-01.
Curtis, A. R., Mogul, J. C., Tourrilhes, J., Yalagandula, P., Sharma, P., and Banerjee, S. (2011). Devoflow: scaling flow management for high-performance networks. In ACM SIGCOMM Computer Communication Review, volume 41, pages 254–265. ACM.
Feamster, N., Rexford, J., and Zegura, E. (2013). The road to sdn. Queue, 11(12):20.
Fishwick, P. A. (1995). Simulation Model Design and Execution: Building Digital Worlds. Prentice Hall PTR, Upper Saddle River, NJ, USA, 1st edition.
Gupta, M., Sommers, J., and Barford, P. (2013). Fast, accurate simulation for sdn prototyping. In Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking, pages 31–36. ACM.
Handigol, N., Heller, B., Jeyakumar, V., Lantz, B., and McKeown, N. (2012). Reproducible network experiments using container-based emulation. In Proceedings of the 8th international conference on Emerging networking experiments and technologies, pages 253–264. ACM.
McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., Shenker, S., and Turner, J. (2008). Openflow: Enabling innovation in campus networks. SIGCOMM Comput. Commun. Rev., 38(2):69–74.
Mello, B. A. and Wainer, G. A. (2016). Scheduling predictability in i-devs by schedulability analysis. Spring Simulation Multi-Conference / Symposium on Theory of Modeling and Simulation (TMS/DEVS), pages 622–629. SCS/ACM.
Molloy, M. K. (1982). Performance analysis using stochastic petri nets. Computers, IEEE Transactions on, 100(9):913–917.
Murata, T. (1989). Petri nets: Properties, analysis and applications. Proceedings of the IEEE, 77(4):541–580.
Puterman, M. L. (2014). Markov decision processes: discrete stochastic dynamic programming. John Wiley & Sons.
R. Gu, E., Li, C., and Wang, R. (2016). Problem statement of sdn and nfv codeployment in cloud datacenters draft-gu-sdnrg-problem-statement-of-sdn-nfv-in-dc-01. https://tools.ietf.org/html/draft-gu-sdnrg-problem-statement-of-sdn-nfv-in-dc-01.
Rexford, J. and Dovrolis, C. (2010). Future internet architecture: Clean-slate versus evolutionary research. Commun. ACM, 53(9):36–40.
Schult, D. A. and Swart, P. (2008). Exploring network structure, dynamics, and function using networkx. In Proceedings of the 7th Python in Science Conferences (SciPy 2008), volume 2008, pages 11–16.
Valmari, A. (1998). The state explosion problem. In Lectures on Petri nets I: Basic models, pages 429–528. Springer.
Wainer, G. (2002). Cd++: a toolkit to develop devs models. Software: Practice and Experience, 32(13):1261–1306.
Wainer, G. A. (2009). Discrete-event modeling and simulation: a practitioner’s approach. CRC Press.
Yu, M., Rexford, J., Freedman, M. J., and Wang, J. (2011). Scalable flow-based networking with difane. ACM SIGCOMM Computer Communication Review, 41(4):351–362.
Zeigler, B. P., Praehofer, H., and Kim, T. G. (2000). Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems. Academic press.
Publicado
04/07/2016
Como Citar
SOUZA, Rafael; SANTOS, Marcelo; MELLO, Braulio; FERNANDES, Stênio.
Um Modelo Formal de Propósito Geral para Simulações de Redes Definidas por Software. In: WORKSHOP PRÉ-IETF (WPIETF), 3. , 2016, Porto Alegre.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 2941-2952.
ISSN 2595-6388.
DOI: https://doi.org/10.5753/wpietf.2016.9739.
