Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks. © 2013 The Brazilian Computer Society.194493510(2007) IEEE 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, , 802.11-2007, Technical report. IEEE Computer Society, New York. doi:10.1109/IEEESTD.2007. 373646. Revision of IEEE Std. 802.11-1999Ancillotti, E., Bruno, R., Conti, M., Experimentation and performance evaluation of rate adaptation algorithms in wireless mesh networks (2008) PE-WASUN: Proceedings of the ACM Symposium On Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous, Networks, pp. 7-14. , doi:10.1145/1454609.1454612Biaz, S., Wu, S., Rate adaptation algorithms for IEEE 802.11 networks: A survey and comparison (2008) ISCC: Proceedings of the IEEE Symposium On Computers And, Communications, pp. 130-136. , doi:10.1109/ISCC.2008.4625680Bicket, J.C., (2005) Bit-rate Selection In Wireless Networks, , http://pdos.csail.mit.edu/papers/jbicket-ms.pdf, Master's thesis. Institute of Technology (MIT), Department of Electrical Engineering and Computer Science, MassachusettsBoyd, J.R., (1995) The Essence of Wining and Losing, , http://pogoarchives.org/m/dni/john_boyd_compendium/essence_of_winning_losing.pdfChaves, L., Malheiros, N., Madeira, E., Garcia, I., Kliazovich, D., A cognitive rate adaptation mechanism for wireless networks (2009) MACE: Proceedings of the IEEE International Workshop On Modelling Autonomic Communication Environments, pp. 58-71. , Springer, Berlin, doi:10.1007/978-3-642-05006-0_5CogProt-the Cognitive Framework, , http://www.lrc.ic.unicamp.br/, cogprotCogTRA-cognitive Transmission Rate Adaptation For OpenWrt, , http://code.google.com/p/cogtraChen, X., Gangwal, P., Qiao, D., Ram: Rate adaptation in mobile environments (2012) IEEE Trans Mobile Comput, 11 (3), pp. 464-477. , doi:10.1109/TMC.2011.91Erez, U., Trott, M.D., Wornell, G.W., Rateless coding for Gaussian channels (2012) IEEE Trans Inf Theory, 58 (2), pp. 530-547. , doi:10. 1109/TIT.2011.2173242Gudipati, A., Katti, S., Strider: Automatic rate adaptation and collision handling. ACM SIGCOMM (2011) Comput Commun Rev, 41 (4), pp. 158-169. , doi:10.1145/2043164.2018455Haratcherev, I., Langendoen, K., Lagendijk, R., Sips, H., Hybrid rate control for IEEE 802.11 (2004) MobiWac: Proceedings of the International Workshop On Mobility Management and Wireless Access Protocols, pp. 10-18. , doi:10.1145/1023783.1023787Heusse, M., Rousseau, F., Berger-Sabbatel, G., Duda, A., Performance anomaly of 802.11b (2003) INFOCOM: Proceedings of the International Conference On Computer Communications, 2, pp. 836-843Holland, G., Vaidya, N., Bahl, P., A rate-adaptive MAC protocol for multi-hop wireless networks (2001) MobiCom: Proceedings of the International Conference On Mobile Computing and Networking, pp. 236-251. , doi:10.1145/381677.381700Hou, J.C., Park, K.J., Kim, T.S., Kung, L.C., Medium access control and routing protocols for wireless mesh networks (2008) Wireless Mesh Networks: Architectures and Protocols, Chap, 4, pp. 77-111. , Hossain E, Leung K, Springer, Berlinhttp://iperf.sourceforge.net, IperfJain, R.K., Chiu, D.M.W., Hawe, W.R., (1984) A Quantitative Measure of Fairness and Discrimination For Resource Allocation In Shared Computer Systems, 301. , http://arxiv.org/abs/cs.NI/9809099, Technical report, Digital Equipment CorporationJoshi, T., Ahuja, D., Singh, D., Agrawal, D.P., SARA: Stochastic automata rate adaptation for IEEE 802.11 networks (2008) IEEE Trans Parallel Distrib Syst, 19 (11), pp. 1579-1590. , doi:10.1109/TPDS.2007. 70814Judd, G., Wang, X., Steenkiste, P., Efficient channel-aware rate adaptation in dynamic environments (2008) MobSys: Proceedings of the International Conference On Mobile Systems, Applications, and Services, pp. 118-131. , doi:10.1145/1378600.1378615Kamerman, A., Monteban, L., Wavelan-II: A high-performance wireless LAN for the unlicensed band (1997) Bell Labs Tech J, 2 (3), pp. 118-133. , doi:10.1002/bltj.2069Kim, J., Kim, S., Choi, S., Qiao, D., CARA: Collision-aware rate adaptation for IEEE 802.11 WLANs (2006) INFOCOM: Proceedings of the International Conference On Computer Communications, pp. 1-11. , doi:10.1109/INFOCOM.2006.316Kim, T.S., Lim, H., Hou, J.C., Improving spatial reuse through tuning transmit power, carrier sense threshold, and data rate in multihop wireless networks (2006) MobiCom: Proceedings of the International Conference On Mobile Computing and Networking, pp. 366-377. , doi:10.1145/1161089.1161131Kliazovich, D., Malheiros, N., Fonseca, N.L.S., Granelli, F., Madeira, E., CogProt: A framework for cognitive configuration and opti mization of communication protocols (2009) Mobilight: Proceedings of the International Conference On Mobile Lightweight Wireless Systems, pp. 280-291. , doi:10.1007/978-3-642-16644-0_25Koci, N., Marina, M., Understanding the role of multi-rate retry mechanism for effective rate control in 802.11 wireless lans (2009) LCN: Proceedings of IEEE Conference On Local, Computer Networks, pp. 305-308. , doi:10.1109/LCN.2009.5355094Lacage, M., Manshaei, M.H., Turletti, T., IEEE 802.11 rate adaptation: A practical approach (2004) MSWiM: Proceedings of the International Symposium On Modeling, Analysis and Simulation of Wireless and Mobile Systems, pp. 126-134. , doi:10.1145/1023663. 1023687Lakshmanan, S., Sanadhya, S., Sivakumar, R., On link rate adaptation in 802.11n WLANs (2011) INFOCOM: Proceedings of the International Conference On Computer Communications, pp. 366-370. , doi:10.1109/INFCOM.2011.5935183Loiacono, M., Rosca, J., Trappe, W., The snowball effect: Detailing performance anomalies of 802.11 rate adaptation (2007) GLOBE-COM: Proceedings of the IEEE Global Telecommunications Conference, pp. 5117-5122. , doi:10.1109/GLOCOM.2007.970Malheiros, N., Kliazovich, D., Granello, F., Madeira, E., Fonseca, N., A Cognitive Approach For Cross-layer Performance Management (2010) GLOBECOM: Proceedings of the IEEE Global Telecom Munications, pp. 1-5. , doi:10.1109/GLOCOM.2010. 5684313OpenWrt Wireless Freedom, , http://openwrt.orgORBIT: Open-access Research Testbed For Next-generation Wireless Networks, , http://www.orbit-lab.orgPerry, J., Balakrishnan, H., Shah, D., Rateless spinal codes (2011) HotNets-X: Proceedings of the ACM Workshop On Hot Topics In Networks, pp. 61-66. , doi:10.1145/2070562.2070568Qiao, D., Choi, S., Shin, K., Goodput analysis and link adaptation for IEEE 802.11a wireless LANs (2002) IEEE Trans Mobile Comput, 1 (4), pp. 278-292. , doi:10.1109/TMC.2002.1175541Ramachandran, K., Kremo, H., Gruteser, M., Spasojevic, P., Seskar, I., Scalability analysis of rate adaptation techniques in congested IEEE 802.11 networks: An ORBIT testbed comparative study (2007) WoWMoM: Proceedings of the IEEE International Symposium On a World of Wireless, Mobile and Multimedia, Networks, pp. 1-12. , doi:10.1109/WOWMOM.2007.4351717Shankar, P., Nadeem, T., Rosca, J., Iftode, L., Cars: Context-aware rate selection for vehicular networks (2008) ICNP: Proceedings of the IEEE International Conference On Network Protocols, pp. 1-12. , doi:10.1109/ICNP.2008.4697019Shannon, C.E., Communication in the presence of noise (1949) IRE Proceedings of the Institute of Radio Engineers, 37 (1), pp. 10-21Smithies, D., (2005) Minstrel Rate Control Algorithm, , http://linuxwireless.org/en/developers/Documentation/mac80211/RateControl/minstrelThomas, R.W., Friend, D.H., Dasilva, L.A., Mackenzie, A.B., Cognitive networks: Adaptation and learning to achieve end-to-end performance objectives (2006) IEEE Commun Mag, 44 (12), pp. 51-57. , doi:10. 1109/MCOM.2006.273099(2011) Federico II, , http://www.grid.unina.it/software/ITG/, Universita' degli Studi di Napoli, D-ITG, distributed internet traffic generatorXia, Q., Hamdi, M., Smart sender: A practical rate adaptation algorithm for multirate, IEEE 802.11 WLANs (2008) IEEE Trans Wirel Commun, 7 (5), pp. 1764-1775. , doi:10.1109/TWC.2008.061047Yin, W., Bialkowski, K., Indulska, J., Hu, P., Evaluations of mad-wifi mac layer rate control mechanisms (2010) IWQoS: Proceedings of the International Workshop On Quality of Service, pp. 1-9. , doi:10. 1109/IWQoS.2010.5542745Yin, W., Hu, P., Indulska, J., Bialkowski, K., Performance of mac80211 rate control mechanisms (2011) MSWiM: Proceedings of the International Conference On Modeling, Analysis and Simulation of Wireless and Mobile Systems, pp. 427-436. , doi:10.1145/ 2068897.2068970