Um método para o diagnóstico do tipo de perda de pacotes em redes sem fio IEEE 802.11
Resumo
Perdas de pacotes são uma ocorrência comum nas redes sem fio. Estas perdas podem ser ocasionadas por colisões ou simplesmente pelo baixo SNR do canal, causando a redução da capacidade da rede e diminuição da vazão. A correta identificação do tipo de perda de pacotes possibilita a otimização do uso do meio. Assim, este trabalho propõe um novo método para identificação do tipo de perda de pacotes em redes sem fio IEEE 802.11. O método introduz bits de controle multiplexados juntamente aos bits de dados do pacote transmitido. No entanto, esses bits de controle são transmitidos de forma mais robusta - e.g., utilizando combinações mais robustas de modulação e codificação - em comparação aos bits de dados. Assim, em caso de perda do pacote, um algoritmo de decisão é executado no receptor. A avaliação realizada mostra que o método proposto possui boa acurácia na identificação do tipo de perda, principalmente para taxas de dados mais elevadas.
Referências
Aman, M. N. and Sikdar, B. (2012). Distinguishing between channel errors and collisions in ieee 802.11. In 2012 46th Annual Conference on Information Sciences and Systems (CISS), pages 1–6.
Bulhões, R. P., Passos, D., and Albuquerque, C. V. N. (2016). Collision probability estimation in wireless networks. In 2016 8th IEEE Latin-American Conference on Communications (LATINCOM), pages 1–6.
Cisco (2020). Cisco annual internet report (2018–2023) white paper.
IEEE (2003). Ieee 802.11g-2003 - ieee standard for information technology – local and metropolitan area networks– specific requirements – part 11: Wireless lan medium access control (mac) and physical layer (phy) specifications: Further higher data rate extension in the 2.4 ghz band.
IEEE (2021). Ieee 802.11ax-2021 – ieee approved draft standard for information technology – telecommunications and information exchange between systems local and metropolitan area networks – specific requirements part 11: Wireless lan medium access control (mac) and physical layer (phy) specifications amendment 1: Enhancements for high efficiency wlan.
Ji-Hoon Yun and Seung-Woo Seo (2006). Collision detection based on re energy duration in ieee 802.11 wireless lan. In 2006 1st International Conference on Communication Systems Software Middleware, pages 1–6.
JuniperResearch (2020). Iot the internet of transformation 2020.
Peng, J., Cheng, L., and Sikdar, B. (2007). A wireless mac protocol with collision detection. IEEE Transactions on Mobile Computing, 6(12):1357–1369.
Rayanchu, S., Mishra, A., Agrawal, D., Saha, S., and Banerjee, S. (2008). Diagnosing wireless packet losses in 802.11: Separating collision from weak signal. In IEEE INFOCOM 2008 - The 27th Conference on Computer Communications, pages 735–743.
Sen, S., Roy Choudhury, R., and Nelakuditi, S. (2012). Csma/cn: Carrier sense multiple access with collision notification. IEEE/ACM Transactions on Networking, 20(2):544–556.
Sen, S., Santhapuri, N., Choudhury, R. R., and Nelakuditi, S. (2010). Accurate: Constellation based rate estimation in wireless networks. In 7th USENIX Symposium on Networked Systems Design and Implementation (NSDI 10), San Jose, CA. USENIX Association.
Vutukuru, M., Balakrishnan, H., and Jamieson, K. (2009). Cross-layer wireless bit rate adaptation. SIGCOMM Comput. Commun. Rev., 39(4):3–14.
Whitehouse, K., Woo, A., Jiang, F., Polastre, J., and Culler, D. (2005). Exploiting the capture effect for collision detection and recovery. In The Second IEEE Workshop on Embedded Networked Sensors, 2005. EmNetS-II., pages 45–52.
Wu, M., Hu, X., Zhang, R., and Yang, L. (2019). Collision recognition in multihop ieee 802.15.4-compliant wireless sensor networks. IEEE Internet of Things Journal, 6(5):8542–8552.
Zeng, Z. and Kumar, P. R. (2008). Towards optimally exploiting physical layer information in ofdm wireless networks. In Proceedings of the 4th Annual International Conference on Wireless Internet, WICON ’08, Brussels, BEL. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).
Zhu, Y. and Sun, Y. (2015). Packet-level failure classification by characterizing failure patterns in wireless sensor networks. In 2015 IEEE Global Communications Conference (GLOBECOM), pages 1–6.
Bulhões, R. P., Passos, D., and Albuquerque, C. V. N. (2016). Collision probability estimation in wireless networks. In 2016 8th IEEE Latin-American Conference on Communications (LATINCOM), pages 1–6.
Cisco (2020). Cisco annual internet report (2018–2023) white paper.
IEEE (2003). Ieee 802.11g-2003 - ieee standard for information technology – local and metropolitan area networks– specific requirements – part 11: Wireless lan medium access control (mac) and physical layer (phy) specifications: Further higher data rate extension in the 2.4 ghz band.
IEEE (2021). Ieee 802.11ax-2021 – ieee approved draft standard for information technology – telecommunications and information exchange between systems local and metropolitan area networks – specific requirements part 11: Wireless lan medium access control (mac) and physical layer (phy) specifications amendment 1: Enhancements for high efficiency wlan.
Ji-Hoon Yun and Seung-Woo Seo (2006). Collision detection based on re energy duration in ieee 802.11 wireless lan. In 2006 1st International Conference on Communication Systems Software Middleware, pages 1–6.
JuniperResearch (2020). Iot the internet of transformation 2020.
Peng, J., Cheng, L., and Sikdar, B. (2007). A wireless mac protocol with collision detection. IEEE Transactions on Mobile Computing, 6(12):1357–1369.
Rayanchu, S., Mishra, A., Agrawal, D., Saha, S., and Banerjee, S. (2008). Diagnosing wireless packet losses in 802.11: Separating collision from weak signal. In IEEE INFOCOM 2008 - The 27th Conference on Computer Communications, pages 735–743.
Sen, S., Roy Choudhury, R., and Nelakuditi, S. (2012). Csma/cn: Carrier sense multiple access with collision notification. IEEE/ACM Transactions on Networking, 20(2):544–556.
Sen, S., Santhapuri, N., Choudhury, R. R., and Nelakuditi, S. (2010). Accurate: Constellation based rate estimation in wireless networks. In 7th USENIX Symposium on Networked Systems Design and Implementation (NSDI 10), San Jose, CA. USENIX Association.
Vutukuru, M., Balakrishnan, H., and Jamieson, K. (2009). Cross-layer wireless bit rate adaptation. SIGCOMM Comput. Commun. Rev., 39(4):3–14.
Whitehouse, K., Woo, A., Jiang, F., Polastre, J., and Culler, D. (2005). Exploiting the capture effect for collision detection and recovery. In The Second IEEE Workshop on Embedded Networked Sensors, 2005. EmNetS-II., pages 45–52.
Wu, M., Hu, X., Zhang, R., and Yang, L. (2019). Collision recognition in multihop ieee 802.15.4-compliant wireless sensor networks. IEEE Internet of Things Journal, 6(5):8542–8552.
Zeng, Z. and Kumar, P. R. (2008). Towards optimally exploiting physical layer information in ofdm wireless networks. In Proceedings of the 4th Annual International Conference on Wireless Internet, WICON ’08, Brussels, BEL. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).
Zhu, Y. and Sun, Y. (2015). Packet-level failure classification by characterizing failure patterns in wireless sensor networks. In 2015 IEEE Global Communications Conference (GLOBECOM), pages 1–6.
Publicado
16/08/2021
Como Citar
CARAPEÇOS, Allysson Chagas; PASSOS, Diego Gimenez.
Um método para o diagnóstico do tipo de perda de pacotes em redes sem fio IEEE 802.11. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 39. , 2021, Uberlândia.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 700-713.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2021.16757.
