Análise do RED e sua Influência na Autossimilaridade do Tráfego de Rede
Resumo
Com a descoberta de que o tráfego da rede possui a característica de autossimilaridade, alguns estudos buscaram diminuí-la, pois essa característica causa alguns efeitos negativos, como maior atraso na fila e congestionamento do tráfego. Entre os fatores trabalhados nas últimas décadas estão algoritmos de gerenciamento de filas, como Random Early Detection (RED). No entanto, os pesquisadores não estudaram a influência do RED na auto-similaridade mais profundamente. Afinal, esse algoritmo possui quatro parâmetros configuráveis (o peso da fila, a probabilidade máxima de queda e os limiares mínimo e máximo), que, quando modificados, podem levar a uma alteração no desempenho e, consequentemente, na autossimilaridade. Portanto, este artigo pretende verificar a influência do RED na auto-similaridade. Para isso, desenvolvemos um padrão para auxiliar na configuração dos limiares de RED. Também, mostramos o impacto de diferentes arranjos de limite na autossimilaridade e no desempenho do tráfego de rede. Além disso, comparamos algumas das melhores configurações de RED com Droptail.
Referências
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Chandra, H., Agarwal, A., and Velmurugan, T. (2010). Analysis of active queue management algorithms their implementation for tcp/ip networks using opnet simulation tool. International Journal of Computer Applications, 6(11):12-15.
Crovella, M. and Bestavros, A. (1997). Self-similarity in World Wide Web traffic: evidence and possible causes. IEEE/ACM Transactions on Networking, 5(6):835-846.
Floyd, S. and Jacobson, V. (1993). Random early detection gateways for congestion avoidance. IEEE/ACM Transactions on networking, 1(4):397-413.
Gharegozi, A. (2010). Experimental evaluation of red queue management mechanism. In 2010 International Conference on Intelligent Network and Computing (ICINC 2010), pages 205-209.
Gong, W.-B., Liu, Y., Misra, V., and Towsley, D. (2005). Self-similarity and long range dependence on the internet: a second look at the evidence, origins and implications. Computer Networks, 48(3):377-399.
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Jeong, H.-D. J., Ahn, W., Kim, H., and Lee, J.-S. R. (2017). Anomalous Traffic Detection and Self-Similarity Analysis in the Environment of ATMSim. Cryptography, 1(3):24.
Kaur, G., Saxena, V., and Gupta, J. (2020). Detection of TCP targeted high bandwidth attacks using self-similarity. Journal of King Saud University Computer and Information Sciences, 32(1):35-49.
Leland, W. E., Taqqu, M. S., Willinger, W., and Wilson, D. V. (1994). On the self-similar nature of ethernet traffic (extended version). IEEE/ACM Transactions on networking, 2(1):1-15.
Lokshina, I., Zhong, H., and Lanting, C. J. M. (2020). Self-similar Teletraffic in a Smart World. In Kryvinska, N. and Gregus, M., editors, Data-Centric Business and Applications, volume 30, pages 137-160. Springer International Publishing, Cham.
Lozhkovskyi, A. (2019). Calculation the service waiting probability with self-similar network traffic. Journal of Engineering Science, 26(2):36-40.
Lysenko, S., Bobrovnikova, K., Matiukh, S., Hurman, I., and Savenko, O. (2020). Detection of the botnets' low-rate DDoS attacks based on self-similarity. International Journal of Electrical and Computer Engineering (IJECE), 10(4):3651.
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Patel, S. (2014). Performance analysis of red for stabilized queue. In 2014 Seventh International Conference on Contemporary Computing (IC3), pages 306-311, Noida, Índia.
Patil, G., McClean, S., and Raina, G. (2011). Drop tail and red queue management with small buffers: stability and hopf bifurcation. ICTACT Journal on Communication Technology, 2(2):339-344.
Paxson, V. and Floyd, S. (1995). Wide area traffic: the failure of Poisson modeling. IEEE/ACM Transactions on Networking, 3(3):226-244.
Rastogi, S. and Zaheer, H. (2016). Comparative analysis of queuing mechanisms: Droptail, red and nlred. Social Network Analysis and Mining, 6(70).
Santhi, V. and Natarajan, A. M. (2011). Active queue management algorithm for tcp networks congestion control. European Journal of Scientific Research, 54(2):245-257.
Sikdar, B., Chandrayana, K., Vastola, K., and Kalyanaraman, S. (2002a). Queue management algorithms and network traffic self-similarity. In Workshop on High Performance Switching and Routing, Merging Optical and IP Technologie, pages 319-323. IEEE.
Sikdar, B., Vastola, K. S., and Kalyanaraman, S. (2002b). On reducing the degree of self-similarity in network traffic. In Proc. IEEE International Conference on Network Protocols, pages 171-180.
Tsybakov, B. and Georganas, N. D. (1998). Self-similar traffic and upper bounds to buffer-overflow probability in an ATM queue. Performance Evaluation, 32(1):57-80.
Yu, S. J., Koh, P., Kwon, H., Kim, D. S., and Kim, H. K. (2016). Hurst parameter based anomaly detection for intrusion detection system. In 2016 IEEE International Conference on Computer and Information Technology (CIT), pages 234-240, Nadi, Fiji.
Adams, R. (2013). Active queue management: A survey. IEEE Communications Surveys and Tutorials, 15(3):1425-1476.
Alkharasani, A. M., Othman, M., Abdullah, A., and Lun, K. Y. (2017). An improved quality-of-service performance using red's active queue management flow control in classifying networks. IEEE Access, 5:24467-24478.
Ammar, D., Begin, T., and Guerin-Lassous, I. (2011). A new tool for generating realistic internet traffic in ns-3. In SIMUTools '11: Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques, pages 81-83. ACM.
Chandra, H., Agarwal, A., and Velmurugan, T. (2010). Analysis of active queue management algorithms their implementation for tcp/ip networks using opnet simulation tool. International Journal of Computer Applications, 6(11):12-15.
Crovella, M. and Bestavros, A. (1997). Self-similarity in World Wide Web traffic: evidence and possible causes. IEEE/ACM Transactions on Networking, 5(6):835-846.
Floyd, S. and Jacobson, V. (1993). Random early detection gateways for congestion avoidance. IEEE/ACM Transactions on networking, 1(4):397-413.
Gharegozi, A. (2010). Experimental evaluation of red queue management mechanism. In 2010 International Conference on Intelligent Network and Computing (ICINC 2010), pages 205-209.
Gong, W.-B., Liu, Y., Misra, V., and Towsley, D. (2005). Self-similarity and long range dependence on the internet: a second look at the evidence, origins and implications. Computer Networks, 48(3):377-399.
Hamdi, M. M., Rashid, S. A., Ismail, M., Altahrawi, M. A., Mansor, M. F., and AbuFoul, M. K. (2018). Performance evaluation of active queue management algorithms in large network. In 2018 IEEE 4th International Symposium on Telecommunication Technologies (ISTT), pages 1-6, Selangor, Malásia.
Jeong, H.-D. J., Ahn, W., Kim, H., and Lee, J.-S. R. (2017). Anomalous Traffic Detection and Self-Similarity Analysis in the Environment of ATMSim. Cryptography, 1(3):24.
Kaur, G., Saxena, V., and Gupta, J. (2020). Detection of TCP targeted high bandwidth attacks using self-similarity. Journal of King Saud University Computer and Information Sciences, 32(1):35-49.
Leland, W. E., Taqqu, M. S., Willinger, W., and Wilson, D. V. (1994). On the self-similar nature of ethernet traffic (extended version). IEEE/ACM Transactions on networking, 2(1):1-15.
Lokshina, I., Zhong, H., and Lanting, C. J. M. (2020). Self-similar Teletraffic in a Smart World. In Kryvinska, N. and Gregus, M., editors, Data-Centric Business and Applications, volume 30, pages 137-160. Springer International Publishing, Cham.
Lozhkovskyi, A. (2019). Calculation the service waiting probability with self-similar network traffic. Journal of Engineering Science, 26(2):36-40.
Lysenko, S., Bobrovnikova, K., Matiukh, S., Hurman, I., and Savenko, O. (2020). Detection of the botnets' low-rate DDoS attacks based on self-similarity. International Journal of Electrical and Computer Engineering (IJECE), 10(4):3651.
Mohammed, H., Attiya, G., and El-Dolil, S. (2017). Active queue management for congestion control: Performance evaluation, new approach, and comparative study. International Journal of Computing and Network Technology, 5(2):37-49.
NS-3 (2020a). ns3::packetsink class reference. https://www.nsnam.org/doxygen/classns3_1_1_packet_sink.html. 22 de Setembro, 2020.
NS-3 (2020b). ns3::queuedisc::stats struct reference. https://www.nsnam.org/doxygen/structns3_1_1_queue_disc_1_1_stats.html. 22 de Setembro, 2020.
Patel, N. and Patel, R. (2019). Performance analysis of network with different queuing mechanisms in tcp/ftp and udp/ftp scenario. In Smart Systems and IoT: Innovations in Computing, pages 13-21. Springer.
Patel, S. (2014). Performance analysis of red for stabilized queue. In 2014 Seventh International Conference on Contemporary Computing (IC3), pages 306-311, Noida, Índia.
Patil, G., McClean, S., and Raina, G. (2011). Drop tail and red queue management with small buffers: stability and hopf bifurcation. ICTACT Journal on Communication Technology, 2(2):339-344.
Paxson, V. and Floyd, S. (1995). Wide area traffic: the failure of Poisson modeling. IEEE/ACM Transactions on Networking, 3(3):226-244.
Rastogi, S. and Zaheer, H. (2016). Comparative analysis of queuing mechanisms: Droptail, red and nlred. Social Network Analysis and Mining, 6(70).
Santhi, V. and Natarajan, A. M. (2011). Active queue management algorithm for tcp networks congestion control. European Journal of Scientific Research, 54(2):245-257.
Sikdar, B., Chandrayana, K., Vastola, K., and Kalyanaraman, S. (2002a). Queue management algorithms and network traffic self-similarity. In Workshop on High Performance Switching and Routing, Merging Optical and IP Technologie, pages 319-323. IEEE.
Sikdar, B., Vastola, K. S., and Kalyanaraman, S. (2002b). On reducing the degree of self-similarity in network traffic. In Proc. IEEE International Conference on Network Protocols, pages 171-180.
Tsybakov, B. and Georganas, N. D. (1998). Self-similar traffic and upper bounds to buffer-overflow probability in an ATM queue. Performance Evaluation, 32(1):57-80.
Yu, S. J., Koh, P., Kwon, H., Kim, D. S., and Kim, H. K. (2016). Hurst parameter based anomaly detection for intrusion detection system. In 2016 IEEE International Conference on Computer and Information Technology (CIT), pages 234-240, Nadi, Fiji.
Publicado
23/05/2022
Como Citar
MORAES, Jorge Magno Lopes; CALLADO, Arthur de Castro.
Análise do RED e sua Influência na Autossimilaridade do Tráfego de Rede. In: WORKSHOP DE GERÊNCIA E OPERAÇÃO DE REDES E SERVIÇOS (WGRS), 27. , 2022, Fortaleza.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 71-84.
ISSN 2595-2722.
DOI: https://doi.org/10.5753/wgrs.2022.223501.
