Abstract
TCP congestion control is essential for improving performance of data transfer. Traditional TCP congestion control algorithm is designed for the wired network with the assumptive goal of attaing higher throughput as possible for QoE. However, Internet today is constantly evolving and many different network architectures (Cellular network, high BDP network, Wi-Fi network, etc.) coexist for data transfer service. Futhermore, the emerging applications (live video, augmented and virtual reality, Internet-of-Things, etc.) present different requirements (low latency, low packet loss rate, low jitter, etc.) for data transfer service. Unfortunately, operating systems (Windows, MacOS, Android, etc.) today still rigidly stick to the single built-in congestion control algorithm (with Cubic for Linux, MacOS, Android and CTCP for Windows) for all connections, no matter if it is ill-suited for current network condition, or if there are better schemes for use. To tackle above issues, we articulate a vision of providing congestion control as a service to enable: (i) timely deployment of novel congestion control algorithms, (ii) dynamical adaption of congestion control algorithm according to the network condition, (iii) and meeting the diversified QoE preference of applications. We design and implement CaaS in Linux, our preliminary experiment shows the feasibility and benefits of CaaS.
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References
Dukkipati, N., Mckeown, N.: Why flow-completion time is the right metric for congestion control. ACM SIGCOMM Comput. Commun. Rev. 36(1), 59–62 (2006)
Kelly, T.: Scalable TCP: improving performance in highspeed wide area networks. ACM SIGCOMM Comput. Commun. Rev. 33(2), 83–91 (2003)
Baiocchi, A., Castellani, A.P., Vacirca, F.: YeAH-TCP: yet another highspeed TCP. In: Proceedings of PFLDnet, Roma, Italy, pp. 37–42 (2007)
Xu, L., Harfoush, K., Rhee, I.: Binary increase congestion control (BIC) for fast long-distance networks. In: INFOCOM 2004. Twenty-Third Annual Joint Conference of the IEEE Computer and Communications Societies. IEEE (2004)
Ha, S., Rhee, I., Xu, L.: CUBIC: a new TCP-friendly high-speed TCP variant. ACM SIGOPS Oper. Syst. Rev. 42(5), 64–74 (2008)
Park, S., et al.: ExLL: an extremely low-latency congestion control for mobile cellular networks. In: The 14th International Conference (2018)
Abbasloo, S., Li, T., Xu, Y., et al.: Cellular Controlled Delay TCP (C2TCP). arXiv, Networking and Internet Architecture (2018)
Floyd, S.: RFC 3649. https://www.ietf.org/rfc/rfc3649.txt. Accessed 10 June 2019
Brakmo, L.S., Peterson, L.L.: TCP Vegas: end to end congestion avoidance on a global Internet. IEEE J. Sel. Areas Commun. 13(8), 1465–1480 (1995)
Caini, C., Firrincieli, R.: TCP Hybla: a TCP enhancement for heterogeneous networks. Int. J. Satell. Commun. Netw. 22(6), 547–566 (2004)
Yan, F.Y., Ma, J., Hill, G.D., et al.: Pantheon: the training ground for internet congestion-control research. In: Usenix Annual Technical Conference, pp. 731–743 (2018)
Tan, K., et al.: A compound TCP approach for high-speed and long distance networks. In: Infocom IEEE International Conference on Computer Communications. IEEE (2007)
Liu, S., Basar, T., Srikant, R.: TCP-Illinois: a loss-and delay-based congestion control algorithm for high-speed networks. Perform. Eval. 65(6), 417–440 (2008)
Cardwell, N., Cheng, Y., et al.: BBR: congestion-based congestion control. ACM Queue 14(5), 20–53 (2016)
Mascolo, S., Casetti, C., et al.: TCP Westwood: bandwidth estimation for enhanced transport over wireless links. In: 7th ACM Conference on Mobile Computing and Networking (MobiCom), Rome, Italy, pp. 287–297 (2001)
Fu, C.P., Liew, S.C.: TCP Veno: TCP enhancement for transmission over wireless access networks. IEEE J. Sel. Area. Commun. 21(2), 216–228 (2003)
Akyildiz, I.F., Zhang, X., et al.: TCP-Peach+: enhancement of TCP-Peach for satellite IP networks. IEEE Commun. Lett. 6(7), 303–305 (2002)
Zaki, Y., Poetsch, T., et al.: Adaptive congestion control for unpredictable cellular networks. ACM SIGCOMM Comput. Commun. Rev. 45(4), 509–522 (2015)
Winstein, K., Balakrishnan, H.: TCP ex Machina: computer-generated congestion control. Comput. Commun. Rev. 43(4), 123–134 (2013)
Jay, N., Rotman, N.H., Godfrey, B., et al.: A deep reinforcement learning perspective on internet congestion control. In: International Conference on Machine Learning, pp. 3050–3059 (2019)
Dong, M., Li, Q., et al.: PCC: re-architecting congestion control for consistent high performance. In: Networked Systems Design and Implementation, pp. 395–408 (2015)
Dong, M., Meng, T., Zarchy, D., et al.: PCC Vivace: online-learning congestion control. In: Networked Systems Design and Implementation, pp. 343–356 (2018)
Linux TCP probe. https://wiki.linuxfoundation.org/networking/tcpprobe. Accessed 12 Oct 2019
Netravali, R., Sivaraman, A., Das, S., et al.: Mahimahi: accurate record-and-replay for HTTP. In: Usenix Annual Technical Conference, pp. 417–429 (2015)
Balakrishnan, H., Stemm, M., et al.: Analyzing stability in wide-area network performance. Meas. Model. Comput. Syst. 25(1), 2–12 (1997)
Jobin, J., Faloutsos, M., et al.: Understanding the effects of hotspots in wireless cellular networks. In: Proceedings of the Conference of the IEEE Computer and Communications Societies, INFOCOM (2004)
Lu, D., Qiao, Y., Dinda, P.A., et al.: Characterizing and predicting TCP throughput on the wide area network. In: IEEE International Conference on Distributed Computing Systems, ICDCS (2005)
Ryan Prescott Adams and David JC MacKay: Bayesian Online Changepoint Detection. In arXiv:0710.3742v1 (2007)
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Zhu, J., Jiang, X., Jin, G., Li, P. (2020). CaaS: Enabling Congestion Control as a Service to Optimize WAN Data Transfer. In: Yu, S., Mueller, P., Qian, J. (eds) Security and Privacy in Digital Economy. SPDE 2020. Communications in Computer and Information Science, vol 1268. Springer, Singapore. https://doi.org/10.1007/978-981-15-9129-7_6
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DOI: https://doi.org/10.1007/978-981-15-9129-7_6
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