A New Method for Measuring Packet Loss Probability Using a Kalman Filter

In this paper, a new packet loss probability (PLP) estimation method is developed based on the Kalman estimation procedure. The Kalman filter is used for the optimal and recursive estimation of the network traffic mean and standard deviation. The estimation is obtained from past measurements to calculate the one-step prediction and is then applied to calculate the PLP parameter with the large-buffer-based estimation formula based on the large deviation theory. The algorithm recursively runs and is applied for the online packet loss control loop, which keeps the PLP parameter under the limit negotiated in the service level agreement with the customer by the Internet service provider. A series of experiments were conducted to evaluate its performance on the live NCIT*net2 network under different traffic arrival models, for two different aggregated traffic rates and different buffer sizes. The numeric results presented in this paper demonstrate the accuracy and effectiveness of the algorithms introduced.

[1]  Edward W. Knightly,et al.  Measurement-based admission control with aggregate traffic envelopes , 2001, TNET.

[2]  Abhay Parekh,et al.  A generalized processor sharing approach to flow control in integrated services networks: the single-node case , 1993, TNET.

[3]  Nicolas D. Georganas,et al.  On self-similar traffic in ATM queues: definitions, overflow probability bound, and cell delay distribution , 1997, TNET.

[4]  Nicolas D. Georganas,et al.  Overflow probability in an ATM queue with self-similar input traffic , 1997, Proceedings of ICC'97 - International Conference on Communications.

[5]  T. V. Lakshman,et al.  What are the implications of long-range dependence for VBR-video traffic engineering? , 1996, TNET.

[6]  Anwar Elwalid,et al.  The Importance of Long-Range Dependence of VBR Video Traffic in ATM Traffic Engineering: Myths and Realities , 1996, SIGCOMM.

[7]  D. Mitra,et al.  Stochastic theory of a data-handling system with multiple sources , 1982, The Bell System Technical Journal.

[8]  ElwalidAnwar,et al.  The importance of long-range dependence of VBR video traffic in ATM traffic engineering , 1996 .

[9]  Franco Blanchini,et al.  Robust rate control for integrated services packet networks , 2002, TNET.

[10]  Matthias Grossglauser,et al.  On the relevance of long-range dependence in network traffic , 1996, SIGCOMM '96.

[11]  Stejarel Veres,et al.  A testbed and research network for next generation services over next generation networks , 2005, First International Conference on Testbeds and Research Infrastructures for the DEvelopment of NeTworks and COMmunities.

[12]  L. Teng.  Theory and application of Kalman filtering , 1970 .

[13]  Zbigniew Dziong,et al.  A framework for bandwidth management in ATM networks—aggregate equivalent bandwidth estimation approach , 1997, TNET.

[14]  Cheng-Shang Chang,et al.  Performance guarantees in communication networks , 2000, Eur. Trans. Telecommun..

[15]  Aleksandar Kolarov,et al.  A control-theoretic approach to the design of an explicit rate controller for ABR service , 1999, TNET.

[16]  Dongli Zhang,et al.  Measurement and Control of Packet Loss Probability for MPLS VPN Services , 2006, IEEE Transactions on Instrumentation and Measurement.

[17]  Nick G. Duffield,et al.  Entropy of ATM Traffic Streams: A Tool for Estimating QoS Parameters , 1995, IEEE J. Sel. Areas Commun..

[18]  D. Ionescu,et al.  A new practical packet loss estimator for MPLS VPN services , 2004, APCC/MDMC '04. The 2004 Joint Conference of the 10th Asia-Pacific Conference on Communications and the 5th International Symposium on Multi-Dimensional Mobile Communications Proceeding.

[19]  Keith McCloghrie,et al.  Management Information Base for network management of TCP/IP-based internets , 1990, RFC.

[20]  Matthias Grossglauser,et al.  On the relevance of long-range dependence in network traffic , 1999, TNET.

[21]  Dongli Zhang,et al.  Packet Loss Probability Estimation with a Kalman Filter Approach , 2006, 2006 IEEE Instrumentation and Measurement Technology Conference Proceedings.

[22]  Frank Kelly,et al.  Notes on effective bandwidths , 1994 .

[23]  R. H. Myers,et al.  Probability and Statistics for Engineers and Scientists , 1978 .

[24]  Dongli Zhang,et al.  On packet loss estimation for virtual private networks services , 2004, Proceedings. 13th International Conference on Computer Communications and Networks (IEEE Cat. No.04EX969).

[25]  Peter Phaal,et al.  InMon Corporation's sFlow: A Method for Monitoring Traffic in Switched and Routed Networks , 2001, RFC.