Available bandwidth estimation is useful for route selection in overlay networks, QoS, and traffic engineer-ing. Many measurement algorithms, such as Pathload, Pathchar, and Packet Transmission Rate (PTR) method, etc. have been proposed. PTR method sends a sequence of packet trains to characterize the interac-tion between probing packets and the competing traffic, and uses the average rate of the packet train as an estimate of the available bandwidth. However, this PTR algorithm does not fully consider the situation that the detection packets lost themselves. This paper improves the original PTR algorithm which considers the specialty of the burst of the network background flow. The improved PTR algorithm uses the method to match the initial gap value and gap step value to solve the problem about the burst of background flow, and the improved PTR algorithm record and control the number of packets with source and destination to solve the lost of some packets. Finally, theory and experiments, verified by the improved algorithm of PTR, can reflect the changes of the network stably and timely under the circumstance of the network fluctuates fre-quently. It improves the accuracy of a network measurement and makes the measurement results, which can reflect the changes of the network more clearly.
References
[1]
S. Banerjee and A. Agrawala, “Estimating available ca-pacity of a network connection [A],” IEEE International Conference on Networks [C], Singapore, pp. 131–138, September 2000. “NetDyn: Network Measutrements Tool,” http://www.CS.umd.edu/suman/netdyn/.
[2]
J. Strauss, D. Katabi, and F. Kaashoek, “A measurement study of available bandwidth estimation tools [A],” Pro-ceedings of ACM Intemet Measurement Conference (IMC) [C], Miami Beach, Florida, October 2003.
[3]
N. N. Hu and P. Steenkiste, “Evaluation and characteriza-tion of available bandwidth probing techniques [J],” IEEE Journal on Selected Areas in Communications, Vol. 21, No. 6, pp. 879–894, August 2003.
[4]
C. Dovrolis, P. Ramanathan, and D. Moore, “What do packet dispersion techniques measure?” in Proceedings of Conference Computer Communication, pp. 905–914, April 2001.
[5]
M. Jain and C. Dovrofis, “End-to-end available band-width: Measurement methodology, dynamics, and rela-tion with TCP throughput [A],” Proceedings of ACM SIGCOMM Symposium on Communication Architec-tures Protocols [C], Pittsburgh, PA, USA, pp. 295–308, August 2002.
[6]
K. Lai and M. Baker, “Nettimer: A tool for measuring bottleneck link bandwidth,” in Proceeding of USENIX Symposium on Internet Technologies and Systems1, pp. 123–134, March 2000.
[7]
R. Prosad, C. Davrolis, M. Murray, et al., “Bandwidth estimation: Metrics measurement techniques and tools [J],” IEEE Network, Vol. 17, No. 6, pp. 27–35, 2003.
[8]
V. Paxson, “Measurements and analysis of end-to-end internet dynamics,” Ph. D. dissertation, Computer Sci-ence Division, U. C. Berkeley, Berkeley, CA, May 1996.
[9]
N. N. Hu and P. Steenkiste, “Estimating available band-width using packet pair probing [J],” Carnegie Mellon University (CMU), 9 September 2002.
[10]
Pasztor A, Veitch D. The Packet Size Dependence of Packet Pair Like Methods[C]. Proc. of IWQoS’ 02, Mi-ami Beach, Florida, USA, 2002.
K. Claffy, G. Miller, and K. Thompson, “The nature of the beast: Recent traffic measurements from an internet backbone,” presented at the ISOC INET Conf., July 1998.
[13]
Y. Zhang, N. Duffield, V. Paxson, and S. Shenker, “On the constancy of Internet path properties,” in Proc. ACM SIGCOMM Internet Measurement Workshop, San Fran-cisco, CA, Nov. 2001, pp. 197–211.
[14]
K. Claffy, G. Miller, and K. Thompson, “The nature of the beast: Recent traffic measurements from an internet backbone,” presented at the ISOC INET Conf., July 1998.
