A Differentiated Pricing Framework for Improving the Performance of the Elastic Traffics in Data Networks

Subject Areas : Embedded Systems

Pejman Goudarzi ¹ ( Research Institute for Information & Communication Technology, Iran )

Received: 2011-08-21 Accepted : 2011-10-17 Published : 2015-02-01

Keywords: AQM, Congestion control, Rate allocation, TCP, fairness,

Abstract :

Rate allocation has become a demanding task in data networks as diversity in users and traffics proliferate. Most commonly used algorithm in end hosts is TCP. This is a loss based scheme therefore it exhibits oscillatory behavior which reduces network performance. Moreover, since the price for all sessions is based on the aggregate throughput, losses that are caused by TCP affect other sessions as well and aggressively reduce their throughput and also have a drastic effect on the overall good put of the system. In this paper a new differentiated pricing method is proposed that not only reduces the loss phenomenon in the network, it improves the overall performance of the network and allows other sessions such as Proportional or Minimum Potential Delay schemes achieve more fair rates. Stability property of the algorithm is investigated and some numerical analysis is presented to verify the claims.

References:

 [1]      D. Katabi, M. Handley, C. Rohrs, “ Internet Congestion Control for High Bandwidth-Delay Product Networks” ACM SIGCOMM 2002.

[2]      C. Jin, D. X. Wei, S. H. Low, “FAST TCP: Motivation, Algorithms, Performance,” INFOCOM 2004.

[3]      M. Nabeshima, “Performance Evaluation of MulTCP in High-Speed Wide Area Networks”, IEICE TRANSACTIONS on Communications  Vol.E88-B  No.1  pp.392-396.

[4]      J. Mo and J. Walrand, “Fair End-to-End Window-Based Congestion Control,” IEEE/ACM Transactions on Networking, vol.8, pp.556-567, no. 5, Oct. 2000.

[5]      FP Kelly, AK Maulloo and DKH Tan, “Rate control for communication networks: shadow prices, proportional fairness and stability,” J. Oper. Res. Soc., vol. 49, no. 3, pp. 237-252, Mar. 1998.

[6]      L. Massoulié and J. Roberts, “Bandwidth sharing : objectives and algorithms,” in  Proc. IEEE INFOCOM, vol.3, 1999, pp. 1395-1403.

[7]      S. Shenker, “Fundamental design issues for the future Internet,” IEEE J Selected Areas Commun., vol.13, no.7, pp.1176-1188, Sept. 1995.

[8]      V. Jacobson, “Congestion avoidance and control,” Comput. Commun.n Rev., vol.18, no. 4, pp. 314-329, Aug. 1988.

[9]      S. Floyd and V. Jacobson, “Connection with multiple congested gateways in packet-switched Networks, Part 1: One-way traffic,” ACM Comput. Commun. Rev., vol.21, no.5, pp. 30-47, Aug. 1991.

[10]   S. Floyd and V. Jacobson, “Random early detection gateways for congestion avoidance,” IEEE/ACM  Trans. Networking, vol.1, pp.397-413, Aug. 1993.

[11]   R.J. Gibbens and F.P. Kelly. (1998,June) Resource pricing and the evolution of congestion control. [Online]. Available: http://www.statslab.cam.ac.uk/~frank

[12]   L.S. Brakmo and L.L. Peterson, “Tcp vegas: End to end congestion avoidance on a global internet,” IEEE J. Select. Areas Commun., vol.13, pp. 1465-1480, Oct. 1995.

[13]   R.J. La  and V. Anantharam, “Utility-Based Rate Control in the Internet for Elastic Traffic,” IEEE Trans. On Networking, vol.10, no.2, pp. 272-286, Apr. 2002.

[14]   J.K. Mackie-Mason and H.R. Varian, “Pricing Congestible Network Resources,” IEEE JSAC, vol.13, No. 7, pp.1141-1149, Sept. 1995. 

[15]   R. Mazumder, L.G. Mason and C. Douligeris, “Fairness in network optimal flow control: optimality of product forms”, IEEE Trans. on Commun. , pp.775-782, Vol. 39, 1991.

[16]   D. Bertsekas and J. Tsitsiklis, Parallel and Distributed Computation. Englewood Cliffs, NJ: Prentice-Hall, 1989.

[17]   F.P. Kelly, Mathematical modeling of the Internet, in Proceedings of the Fourth International Congress on Industrial and Applied Mathematics, 1999