Take a look at the new version of this page: [ beta version ]. Tell us what you think.

ABSTRACT

Techniques for modeling and simulating channel conditions play an essential role in understanding network protocol and application behavior. In [11], we demonstrated that inaccurate modeling using a traditional analytical model yielded significant errors in error control protocol parameters choices. In this paper, we demonstrate that time-varying effects on wireless channels result in wireless traces which exhibit non-stationary behavior over small window sizes. We then present an algorithm that divides traces into stationary components in order to provide analytical channel models that, relative to traditional approaches, more accurately represent characteristics such as burstiness, statistical distribution of errors, and packet loss processes. Our algorithm also generates artificial traces with the same statistical characteristics as actual collected network traces. For validation, we develop a channel model for the circuit-switched data service in GSM and show that it: (1) more closely approximates GSM channel characteristics than a traditional Gilbert model and (2) generates artificial traces that closely match collected traces' statistics. Using these traces in a simulator environment enables future protocol and application testing under different controlled and repeatable conditions.

REFERENCES

• 1: BALAKRISHNAN, H., AND KATZ, R. Explicit loss notification and wireless web performance. In Proceedings of the IEEE Globecom hzternet Mini-Coaference (November 1998).
• 2: Julius S. Bendat , Allan G. Piersol, Random Data: Analysis and Measurement Procedures, John Wiley & Sons, Inc., New York, NY, 1990
• 3: BOLOT, J., FOSSE-PARISIS, S., AND D.TOWSLEY. Adaptive FEC- based error control for internet telephony. Proc. lnfocom "99 (March 1999).
• 4: George Edward Pelham Box , Gwilym M. Jenkins, Time Series Analysis: Forecasting and Control, Prentice Hall PTR, Upper Saddle River, NJ, 1994
• 5: ETSI GSM TECHNICAL SPECIFICATION 04.22. GSM Radio Link Protocol for data and telematic services, Version 5, December 1995.
• 6: ETSI GSM TECHNICAL SPECIFICATION 04.22. Digital cellular communications system (Phase 2+); Radio Link Protocol for data and telematic services on the Mobile Station-Base Station Systems(MS-BSS) Interface and the Base Station System-Mobile Switching Center (BSS-MSC) interface, Version 6.1.0, November 1998.
• 7: ETSI GSM TECHNICAL SPECIFICATION 04.22. GSM Radio Link Protocol for data and telematic services, Version 6.1, November 1998.
• 8: ETSI GSM TECHNICAL SPECIFICATION 05.03. Digital cellular communications system (GSM Radio Access Phase 3); Channel coding, Version 6.0.0, January 1998.
• 9: JAIN, R. The Art of Computer Systems Performance Analysis. John Wiley and Sons, 1991.
• 10: KEDEM, B. Binary Time Series. New York and Basel, 1980.
• 11: Reiner Ludwig , Almudena Konrad , Anthony D. Joseph, Optimizing the end-to-end performance of reliable flows over wireless links, Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking, p.113-119, August 15-19, 1999, Seattle, Washington, United States [doi>10.1145/313451.313513]
• 12: LUDWIG, R., AND RATHONYI, B. Link layer enhancements for TCP/IP over GSM. In Proceedings oflEEE INFOCOM (1999).
• 13: MANDELBROT, B. Self-similar error clusters in communication systems and the concept of conditional stationarity. IEEE Transactions on Communication Technology COM-13 (1965), 71-90.
• 14: MERHAV, N., GUTMAN, M., AND ZIV, J. On the estimation of the order of a Markov chain and universal data compression. IEEE Trans. on Information Technology 35, 5 (September 1989), 1014-1019.
• 15: Michel Mouly , Marie-Bernadette Pautet , Thomas Haug, The GSM System for Mobile Communications, Telecom Publishing, 1992
• 16: Giao T. Nguyen , Randy H. Katz , Brian Noble , Mahadev Satyanarayanan, A trace-based approach for modeling wireless channel behavior, Proceedings of the 28th conference on Winter simulation, p.597-604, December 08-11, 1996, Coronado, California, United States [doi>10.1145/256562.256764]
• 17: ROSS, S. M. Stochastic Processes. John Wiley and Sons, 1996.
• 18: SIMPSON, W. The point-to-point protocol. RFC 1661 (Jul 1994).
• 19: W. Richard Stevens, TCP/IP illustrated (vol. 1): the protocols, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1993
• 20: M. Yajnik , J. Kurose , D. Towsley, Packet Loss Correlation in the MBone Multicast Networ Experimental Measurements and Markov Chain Models, University of Massachusetts, Amherst, MA, 1995
• 21: ZORZI, M., AND RAO, R. R. On the statistics of block errors in bursty channels. In IEEE Transactions on Communications (1997).

INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Wireless communication

Additional Classification:
  B. Hardware
  B.4 INPUT/OUTPUT AND DATA COMMUNICATIONS
      B.4.2 Input/Output Devices
          Subjects: Channels and controllers

  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS

  I. Computing Methodologies
  I.6 SIMULATION AND MODELING

General Terms:
Algorithms, Design, Measurement, Performance, Standardization, Theory