基于自相似模型的网络传输层拥塞控制算法
摘要
随着计算机技术和因特网的进一步发展，人们不但对于网络所能提供的数据传输等传统业务具有很大的兴趣，更对网络中视频，语音等多媒体业务表现出了更高的热情。与此同时，随着网络中业务类型的不断丰富，问题也接踵而来。多媒体业务流会给整个网络的性能带来极大的影响，如：多媒体业务导致网络流自相似现象加重，使网络的原有的Markov模型基础上的协议、策略，及其评价方法不够准确，导致丢失率上升，网络性能下降； 多媒体业务中使用的大量UDP包与普通数据流TCP包共存时对公平性的影响等等。令人遗憾的是，至今，针对这些不利因素所提出有效的解决方案寥寥无几。这是因为最初设计网络时主要是追求简单易用和稳定的特征，在下层中所能得到的接口和控制手段相对很少；同时，作为上层基础的已经即成事实的下层协议，人们也不可能在短时间内作太多的改变，只能寻求逐步的更新。而在上层网络，人们虽然一直致力于研究应用层的服务质量保证及其相关的协议问题，但这些大多只是为了个别的业务类型和用户服务，对整体的网络性能贡献有限。
本文针对网络中的这一难题，通过对长相关业务流的统计分析和多种原有网络协议的研究，提出了一系列适应新网络环境的基于预测的传输层TCP改进算法，并通过了在NS2仿真平台上的精确仿真验证了其有效性。尤其值得一提的是：新算法的引入并不需要放弃已经广泛应用的各种协议，也不会在旧协议中增加任何不可接受的字段，唯一的工作只是在发送端添加相应的简单代码。仿真结果证明：新算法不但能在多媒体业务流占主导的网络环境下提高网络的性能(主要体现在网络整体带宽的利用率大大提高上)，而且在普通的数据网络中同样有效，同时在短相关的网络环境下不会带来性能的下降。
With the development of computer science and internet, people are not only focusing the interests on traditional data transfer in network but also multimedia traffics such as audio and video. At the same time, it may also bring some troubles. For instance, a new property of network traffic (self-similarity) has been observed in diverse networking contexts. Some old protocols, policies and evaluate methods which are based on previous Markov network model are not suitable for this self-similar traffic. And when TCP data share bandwidth with UDP data that is popular for multimedia applications over the internet, it also causes fairness problem. However, even recently, these are not many excellent solutions. It is because that network designers have left few control interfaces in the lower layer of the network, and network users have strong unwillingness to make major changes on the accustomed protocols. In the upper layer of the network, there do exist some control methods, but most of them only forcus on the QoS of a single connectionand make very little contribution to the total network.
In this paper, based on analysis of network protocols and property of self-similarity in the network traffic, a class of new algorithms of congestion control is presented and theoretically analyzed. The new algorithms need not to add any unacceptable matters in old protocol, it only need a few changes on the codes at the traffic sender. Simulation results show that network performance is improved in different long-range dependent network circumstances and not worse than the old algorithm when applied in short-range dependent network environment.
本文针对网络中的这一难题，通过对长相关业务流的统计分析和多种原有网络协议的研究，提出了一系列适应新网络环境的基于预测的传输层TCP改进算法，并通过了在NS2仿真平台上的精确仿真验证了其有效性。尤其值得一提的是：新算法的引入并不需要放弃已经广泛应用的各种协议，也不会在旧协议中增加任何不可接受的字段，唯一的工作只是在发送端添加相应的简单代码。仿真结果证明：新算法不但能在多媒体业务流占主导的网络环境下提高网络的性能(主要体现在网络整体带宽的利用率大大提高上)，而且在普通的数据网络中同样有效，同时在短相关的网络环境下不会带来性能的下降。
With the development of computer science and internet, people are not only focusing the interests on traditional data transfer in network but also multimedia traffics such as audio and video. At the same time, it may also bring some troubles. For instance, a new property of network traffic (self-similarity) has been observed in diverse networking contexts. Some old protocols, policies and evaluate methods which are based on previous Markov network model are not suitable for this self-similar traffic. And when TCP data share bandwidth with UDP data that is popular for multimedia applications over the internet, it also causes fairness problem. However, even recently, these are not many excellent solutions. It is because that network designers have left few control interfaces in the lower layer of the network, and network users have strong unwillingness to make major changes on the accustomed protocols. In the upper layer of the network, there do exist some control methods, but most of them only forcus on the QoS of a single connectionand make very little contribution to the total network.
In this paper, based on analysis of network protocols and property of self-similarity in the network traffic, a class of new algorithms of congestion control is presented and theoretically analyzed. The new algorithms need not to add any unacceptable matters in old protocol, it only need a few changes on the codes at the traffic sender. Simulation results show that network performance is improved in different long-range dependent network circumstances and not worse than the old algorithm when applied in short-range dependent network environment.
引文
[1] Saleem N.Bhatti, Graham Knight. Enabling QoS adaptation decisions for Internet applications. Computer Networks, 1999, 31:669-692
[2] Jhyda Lin ,Ruay_shiung chang. A comparison fo the Internet multicast routing protocols. Computer Communications , 1999, 22:144-155
[3] Ken carberg, Jon crowcroft. Burlding chared trees using a one-to-many jioning mechanism. Computer Communication Review, 1997, 27
[4] Rajib Ghosh, George Varghese. Congestion Control in Multicast Transport Protocols. Washington Univ, 1998, http://citeseer.nj.nec.com/169032.html
[5] Tony Speakman,Dio Farinacci, Steven Lin, and Slex Tweedly. PGM Reliable Transport Protocol. Internet Draft:Draft-speakman-pgm-spec-01.txt, January 1998. Expires July 1998
[6] Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z., Weiss,W. An Architecture for Differentiated Services , RFC2475, December 1998
[7] Braden. R., Clark, D., Shenker, S. Integrated Services in the Internet Architecture: an Overview. RFC1633, June 1994.
[8] Leland,W.E.,Taqqu,M.S.Willinger,W. and Wilson,D.V. On the self-Similar Nature of Ethernet Traffic. IEEE Transactions on Networking, 1994, 1:1-15
[9] Beran,J.,Sherman,R., Taqqu,M.S.Willinger,W. Long-Range Dependence in Variable-Bit Rate Video Traffic. IEEE Transactions on Communications, 1995, 43:1566-1579
[10] Crovella,M.E and Bestavros,A,. Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes. In Proceedings of ACM SIGMETRICS'96, 1996,. 160-169
[11] Duffy D.E.,Rosenstein,M. and Willinger,W. Statistical Analysis of CCSN/SS7 Traffic Data from Working Subnetworks, IEEE Journal on Selected Areas in Communications, 1994, 3:544-551
[12] Boris Tsybabov, Nicolas D. Self-similar Processes in Communications network. IEEE Transaction on Information Theory, 1998, 5: 1713-1725
[13] T.Tuan,K,Park. Multiple Time Scale Congestion Control for Self-Similar Network Traffic. Dept of comp Sci Pcodue Univ, 10 May 1999 ,to be published.
[14] Jan Beran. Statistic for Long-Memory Processes. Chapman & Hall，1994.
[15] Vern Paxson. Fast，Approximate Synthesis of Fractional Gaussian Noise for Generating Self-Similar Network Traffic. Computer Communication Review，1997，5(3):5~18.
[16] Murad S. Taqqu，Vadim Teverovsky，and Walter Willinger. Is Network Traffic Self-simlar or Multifractal? Preprint 1996.
[17] Ilkka Norros. On the Use of Fractional Brownian Motion in the Theory of Connectionless Networks. IEEE Journal on Selected Areas in Communications，1995，13(6) :953~962
[18] Vern Paxson and Sally Floyd. Wide-Area Traffic: The Failure of Poisson Modeling. IEEE/ACM Transactions on Networking, 1995, 3:226-244
[19] Garrett Metal. Analysis, modeling and generation of self similar VBR video traffic. In: Proc of SIGCOMM'94. London, 1994, 269-280.
[20] T. Hettmansperger, and M. Keenan. Tailweight, Statistical Inference, and Families of Distributions - A Brief Survey. Statistical Distributions in Scientific Work, 1980, 1:161-172
[21] M. Garrett. Contributions Toward Real-Time Services on Packet Switched Networks. CU/CTR/TR 340-93-20, Columbia University, 1993, p.96
[22] Jan Beran. A Test of Location for Data with Slowly Decaying Serial Correlations. Biometrika, 1989, 76:261-269
[23] J.Mark Pullen. The Network Workbench: network simulation software for academic investigation of Internet concepts. Computer Network, 2000, 32: 365-378
[24] Kevin Fall,Kannan Varadhan. The ns Manual (formerly ns Notes and Documentation). The VINT Project, Aug. 2001
http://www.isi.edu/ nsnam/ns/ns-documentation.html
[25] http://www.isi.edu/nsnam/dist/ns-src-2.1b8.tar.gz
[26] Brent B.Welch. Tcl/Tk 组合教程（第二版）. 电子科技出版社，2001
[27] Kevin Fall and Sally Floyd. Simulation-based Comparisons of Tahoe, Reno and SACK TCP. ACM Computer Communication Review, 1996,Vol.26, No.4
[28] http://www.isi.edu/nsnam/nam/nam2.html #TUTORIAL
[29] http://www.isi.edu/nsnam/xgraph/
[30] http://www.isi.edu/nsnam/archive/ns-users/webarch/
[31] I. Katzela. Modeling and Simulating Communications Networks. Prentice-Hall, Englewood Cliffs, NJ, 1999
[32] Zafer Sshinoglu. On multimedia network: self-similar traffic and network performance. IEEE Communications Magazine, 1999, 1:48-52
[33] Parag Pruthi and Adrian Popescu. Effect of Controls on Self-Similar Traffic. University of Karlskrona Department of Telecommunications and Mathematics 371 79 Karlskrona, Sweden , June 18,1997.
[34] Sally Floyd. Promoting the Use of End-to-End Congestion Control in the Internet. IEEE/ACM Transactions on Networking, 1999, 44:58-472
[35] Andrew S. Tanenbaum. Computer Networks (Third Edition). Prentice Hall PTR 1996
[36] Information Sciences Institute University of Southern California. TRANSMISSION CONTROL PROTOCOL. DARPA INTERNET PROGRAM. September 1981
[37] V.Jacobson. Modified TCP Congestion Avoidance Algorithm. Technical report, 30 Apr 1990. URL: ftp://ftp.ee.lbl.gov/email/vanj.90apr30.txt
[38] Chikara OHTA and Fumio ISHIZAKI. Output Process of Shaper and Switch With Self-Similar Traffic in ATM Networks. IEICE Trans. Communication, 1998, 10:1936-1940
[39] L. Brakmo and L. Peterson. TCP Vegas: End to End Congestion Avoidance on a Global Internet. IEEE Journal of Selected Areas in Communications, 1995, 8: 1465-1480
[40] Toshihiko KATO, Akira KIMURA, Teruyuki HASWGAWA and Kenji SUZUKI. A Continuous Media Transfer Protocol With Congestion Control Using Two Level Rate Control. IEICE TRANS.COMMUN., 1999, 6: 827-833
[41] 王宇, 赵千川, 郑大钟, 基于自相似的TCP拥塞控制算法, 通信学报, 2001, 5:31-38
[2] Jhyda Lin ,Ruay_shiung chang. A comparison fo the Internet multicast routing protocols. Computer Communications , 1999, 22:144-155
[3] Ken carberg, Jon crowcroft. Burlding chared trees using a one-to-many jioning mechanism. Computer Communication Review, 1997, 27
[4] Rajib Ghosh, George Varghese. Congestion Control in Multicast Transport Protocols. Washington Univ, 1998, http://citeseer.nj.nec.com/169032.html
[5] Tony Speakman,Dio Farinacci, Steven Lin, and Slex Tweedly. PGM Reliable Transport Protocol. Internet Draft:Draft-speakman-pgm-spec-01.txt, January 1998. Expires July 1998
[6] Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z., Weiss,W. An Architecture for Differentiated Services , RFC2475, December 1998
[7] Braden. R., Clark, D., Shenker, S. Integrated Services in the Internet Architecture: an Overview. RFC1633, June 1994.
[8] Leland,W.E.,Taqqu,M.S.Willinger,W. and Wilson,D.V. On the self-Similar Nature of Ethernet Traffic. IEEE Transactions on Networking, 1994, 1:1-15
[9] Beran,J.,Sherman,R., Taqqu,M.S.Willinger,W. Long-Range Dependence in Variable-Bit Rate Video Traffic. IEEE Transactions on Communications, 1995, 43:1566-1579
[10] Crovella,M.E and Bestavros,A,. Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes. In Proceedings of ACM SIGMETRICS'96, 1996,. 160-169
[11] Duffy D.E.,Rosenstein,M. and Willinger,W. Statistical Analysis of CCSN/SS7 Traffic Data from Working Subnetworks, IEEE Journal on Selected Areas in Communications, 1994, 3:544-551
[12] Boris Tsybabov, Nicolas D. Self-similar Processes in Communications network. IEEE Transaction on Information Theory, 1998, 5: 1713-1725
[13] T.Tuan,K,Park. Multiple Time Scale Congestion Control for Self-Similar Network Traffic. Dept of comp Sci Pcodue Univ, 10 May 1999 ,to be published.
[14] Jan Beran. Statistic for Long-Memory Processes. Chapman & Hall，1994.
[15] Vern Paxson. Fast，Approximate Synthesis of Fractional Gaussian Noise for Generating Self-Similar Network Traffic. Computer Communication Review，1997，5(3):5~18.
[16] Murad S. Taqqu，Vadim Teverovsky，and Walter Willinger. Is Network Traffic Self-simlar or Multifractal? Preprint 1996.
[17] Ilkka Norros. On the Use of Fractional Brownian Motion in the Theory of Connectionless Networks. IEEE Journal on Selected Areas in Communications，1995，13(6) :953~962
[18] Vern Paxson and Sally Floyd. Wide-Area Traffic: The Failure of Poisson Modeling. IEEE/ACM Transactions on Networking, 1995, 3:226-244
[19] Garrett Metal. Analysis, modeling and generation of self similar VBR video traffic. In: Proc of SIGCOMM'94. London, 1994, 269-280.
[20] T. Hettmansperger, and M. Keenan. Tailweight, Statistical Inference, and Families of Distributions - A Brief Survey. Statistical Distributions in Scientific Work, 1980, 1:161-172
[21] M. Garrett. Contributions Toward Real-Time Services on Packet Switched Networks. CU/CTR/TR 340-93-20, Columbia University, 1993, p.96
[22] Jan Beran. A Test of Location for Data with Slowly Decaying Serial Correlations. Biometrika, 1989, 76:261-269
[23] J.Mark Pullen. The Network Workbench: network simulation software for academic investigation of Internet concepts. Computer Network, 2000, 32: 365-378
[24] Kevin Fall,Kannan Varadhan. The ns Manual (formerly ns Notes and Documentation). The VINT Project, Aug. 2001
http://www.isi.edu/ nsnam/ns/ns-documentation.html
[25] http://www.isi.edu/nsnam/dist/ns-src-2.1b8.tar.gz
[26] Brent B.Welch. Tcl/Tk 组合教程（第二版）. 电子科技出版社，2001
[27] Kevin Fall and Sally Floyd. Simulation-based Comparisons of Tahoe, Reno and SACK TCP. ACM Computer Communication Review, 1996,Vol.26, No.4
[28] http://www.isi.edu/nsnam/nam/nam2.html #TUTORIAL
[29] http://www.isi.edu/nsnam/xgraph/
[30] http://www.isi.edu/nsnam/archive/ns-users/webarch/
[31] I. Katzela. Modeling and Simulating Communications Networks. Prentice-Hall, Englewood Cliffs, NJ, 1999
[32] Zafer Sshinoglu. On multimedia network: self-similar traffic and network performance. IEEE Communications Magazine, 1999, 1:48-52
[33] Parag Pruthi and Adrian Popescu. Effect of Controls on Self-Similar Traffic. University of Karlskrona Department of Telecommunications and Mathematics 371 79 Karlskrona, Sweden , June 18,1997.
[34] Sally Floyd. Promoting the Use of End-to-End Congestion Control in the Internet. IEEE/ACM Transactions on Networking, 1999, 44:58-472
[35] Andrew S. Tanenbaum. Computer Networks (Third Edition). Prentice Hall PTR 1996
[36] Information Sciences Institute University of Southern California. TRANSMISSION CONTROL PROTOCOL. DARPA INTERNET PROGRAM. September 1981
[37] V.Jacobson. Modified TCP Congestion Avoidance Algorithm. Technical report, 30 Apr 1990. URL: ftp://ftp.ee.lbl.gov/email/vanj.90apr30.txt
[38] Chikara OHTA and Fumio ISHIZAKI. Output Process of Shaper and Switch With Self-Similar Traffic in ATM Networks. IEICE Trans. Communication, 1998, 10:1936-1940
[39] L. Brakmo and L. Peterson. TCP Vegas: End to End Congestion Avoidance on a Global Internet. IEEE Journal of Selected Areas in Communications, 1995, 8: 1465-1480
[40] Toshihiko KATO, Akira KIMURA, Teruyuki HASWGAWA and Kenji SUZUKI. A Continuous Media Transfer Protocol With Congestion Control Using Two Level Rate Control. IEICE TRANS.COMMUN., 1999, 6: 827-833
[41] 王宇, 赵千川, 郑大钟, 基于自相似的TCP拥塞控制算法, 通信学报, 2001, 5:31-38
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