Um método para o diagnóstico do tipo de perda de pacotes em redes sem fio IEEE 802.11
Abstract
Packet losses are a common occurrence on wireless networks. These packet losses can be caused by collisions or simply by the low SNR of the channel, causing a decrease in the network capacity and throughput. The correct identification of the type of packet loss makes it possible to optimize the use of the medium. Thus, this work proposes a new method for identifying the type of packet losses in IEEE 802.11 networks. The method introduces control bits that are multiplexed along with the transmitted frames. However, those control bits are sent in a more robust fashion — e.g., with more robust combinations of modulation and coding - in comparison to the data bits. Then, in case of loss, a decision algorithm is executed on the receiver. Our evaluation shows that the proposed method has good accuracy in identifying the type of packet loss, especially for higher data rates.
References
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.
Published
2021-08-16
How to Cite
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: BRAZILIAN SYMPOSIUM ON COMPUTER NETWORKS AND DISTRIBUTED SYSTEMS (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.
