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ABSTRACT

We study the time-scaling characteristics of low-power wireless communication at the physical and link layers. We observe that links are bursty at many time scales: the packet reception rate (PRR) varies regardless of the length of the time scale considered. Using wavelet analysis, we find that RSSI variations in many wireless sensor network (WSN) links are consistent with statistical self-similarity but not with long range dependence, which can explain burstiness at many scales. We relate RSSI variance to the probability that the physical layer is consistent with self-similarity. Current simulation models and protocols do not take these characteristics into account, leading to inaccurate simulation and sub-optimal protocol performance.

REFERENCES

• 1: P. Abry, P. Flandrin, M. Taqqu, and D. Veitch. Wavelets for the analysis, estimation, and synthesis of scaling data. In K. Park and W. Willinger, editors, Self-Similar Network Traffic and Performance Evaluation, pages 39--88. Wiley, 2000.
• 2: Daniel Aguayo , John Bicket , Sanjit Biswas , Glenn Judd , Robert Morris, Link-level measurements from an 802.11b mesh network, ACM SIGCOMM Computer Communication Review, v.34 n.4, October 2004 [doi>10.1145/1030194.1015482]
• 3: B. N. Chun , P. Buonadonna , A. AuYoung , Chaki Ng , D. C. Parkes , J. Shneidman , A. C. Snoeren , A. Vahdat, Mirage: a microeconomic resource allocation system for sensornet testbeds, Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors, p.19-28, April 30-May 01, 2005
• 4: Will E. Leland , Murad S. Taqqu , Walter Willinger , Daniel V. Wilson, On the self-similar nature of Ethernet traffic (extended version), IEEE/ACM Transactions on Networking (TON), v.2 n.1, p.1-15, Feb. 1994 [doi>10.1109/90.282603]
• 5: Tal Rusak , Philip A. Levis, Investigating a physically-based signal power model for robust low power wireless link simulation, Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems, October 27-31, 2008, Vancouver, British Columbia, Canada [doi>10.1145/1454503.1454514]
• 6: K. Srinivasan, P. Dutta, A. Tavakoli, and P. Levis. Some implications of low-power wireless to IP routing. In HotNets V, 2006.
• 7: Kannan Srinivasan , Maria A. Kazandjieva , Saatvik Agarwal , Philip Levis, The β-factor: measuring wireless link burstiness, Proceedings of the 6th ACM conference on Embedded network sensor systems, November 05-07, 2008, Raleigh, NC, USA [doi>10.1145/1460412.1460416]
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INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.4 PERFORMANCE OF SYSTEMS
      Subjects: Modeling techniques

Additional Classification:
  G. Mathematics of Computing
  G.3 PROBABILITY AND STATISTICS
      Subjects: Time series analysis

  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.1 Simulation Theory

General Terms:
Experimentation, Measurement, Performance

Keywords:
wavelet analysis, wireless sensor networks