Kannan Srinivasan
ABSTRACT
Measuring 802.15.4 reception in three testbeds, we find that most intermediate links are bursty: they shift between poor and good delivery. We present a metric to measure this link burstiness and name it β. We find that link burstiness affects protocol performance and that β can predict the effects. We show that measuring β allows us to reason about how long a protocol should pause after encountering a packet failure to reduce its transmission cost. We find that using β as a guide to setting a single constant in a standard sensor network data collection protocol reduces its average transmission cost by 15%. In addition to data from 802.15.4 testbeds, we examine traces from 802.11b networks and find β has a broader relevance in the wireless domain.
- ANSI/IEEE Std 802.11 1999 Edition.Google Scholar
- D. Aguayo, J. C. Bicket, S. Biswas, G. Judd, and R. Morris. Link-level measurements from an 802.11b mesh network. In SIGCOMM, pages 121--132, 2004. Google ScholarDigital Library
- A. Cerpa. Low-power wireless links properties: Modeling and applications in sensor networks. In PhD thesis, University of California, Los Angeles, California, 2005. Google ScholarDigital Library
- A. Cerpa, N. Busek, and D. Estrin. Scale: A tool for simple connectivity assessment in lossy environments. Technical Report 0021, Sept. 2003.Google Scholar
- A. Cerpa, J. L. Wong, M. Potkonjak, and D. Estrin. Temporal properties of low power wireless links: modeling and implications on multi-hop routing. In MobiHoc '05: Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing, 2005. Google ScholarDigital Library
- ChipCon Inc. CC2420 Data Sheet. http://www.chipcon.com/files/CC2420_Data_Sheet_1_4.pdf, 2006.Google Scholar
- D. S. J. D. Couto, D. Aguayo, J. Bicket, and R. Morris. A high-throughput path metric for multi-hop wireless routing. In MobiCom '03: Proceedings of the 9th annual international conference on Mobile computing and networking, 2003. Google ScholarDigital Library
- S. Cui and A. J. Goldsmith. Cross-layer design of energy-constrained networks using cooperative mimo techniques. Signal Process., 86(8):1804--1814, 2006. Google ScholarDigital Library
- R. Fonseca, O. Gnawali, K. Jamieson, S. Kim, P. Levis, and A. Woo. TEP 123: Collection Tree Protocol. http://www.tinyos.net/tinyos-2.x/doc/.Google Scholar
- R. Fonseca, O. Gnawali, K. Jamieson, and P. Levis. "four bit wireless link estimation. In The Sixth Workshop on Hot Topics in Networks (HotNets-VI), Nov. 2007.Google Scholar
- E. N. Gilbert. Capacity of a burst-noise channel. Bell System Tecnical Journal, 39:1253--1266, 1960.Google ScholarCross Ref
- A. Goldsmith. Wireless Communications. Cambridge University Press, New York, NY, USA, 2005. Google ScholarDigital Library
- J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. E. Culler, and K. S. J. Pister. System Architecture Directions for Networked Sensors. In Architectural Support for Programming Languages and Operating Systems, pages 93--104, 2000. TinyOS is available at http://webs.cs.berkeley.edu. Google ScholarDigital Library
- Intel Research Berkeley. Mirage testbed. https://mirage.berkeley.intel-research.net/.Google Scholar
- R. Jain and S. Routhier. Packet trains--measurements and a new model for computer network traffic. In IEEE Journal on Selected Areas in Communications, volume 4, September 1986.Google ScholarDigital Library
- K. Jamieson and H. Balakrishnan. PPR: Partial Packet Recovery for Wireless Networks. In ACM SIGCOMM, Kyoto, Japan, August 2007. Google ScholarDigital Library
- C. Jiao, L. Schwiebert, and B. Xu. On modeling the packet error statistics in bursty channels. In LCN '02: Proceedings of the 27th Annual IEEE Conference on Local Computer Networks, pages 534--541, Washington, DC, USA, 2002. IEEE Computer Society. Google ScholarDigital Library
- M. Kim and B. Noble. Mobile network estimation. In MobiCom '01: Proceedings of the 7th annual international conference on Mobile computing and networking, pages 298--309, New York, NY, USA, 2001. ACM Press. Google ScholarDigital Library
- A. Köpke, A. Willig, and H. Karl. Chaotic maps as parsimonious bit error models of wireless channels. In Proc. of IEEE INFOCOM, San Francisco, USA, Mar. 2003.Google ScholarCross Ref
- H. Lee, A. Cerpa, and P. Levis. Improving wireless simulation through noise modeling. In IPSN '07: Proceedings of the 6th international conference on Information processing in sensor networks, 2007. Google ScholarDigital Library
- S. Lin, J. Zhang, G. Zhou, L. Gu, J. A. Stankovic, and T. He. Atpc: adaptive transmission power control for wireless sensor networks. In Proceedings of the 4th international conference on Embedded networked sensor systems, pages 223--236, 2006. Google ScholarDigital Library
- M. Mushkin and I. Bar-David. Capacity and Coding for the Gilbert- Elliott Channels. IEEE Transactions on Information Theory, 35:1277--1290, 1989.Google ScholarDigital Library
- C. Reis, R. Mahajan, M. Rodrig, D. Wetherall, and J. Zahorjan. Measurement-based models of delivery and interference in static wireless networks. In SIGCOMM, pages 51--62, 2006. Google ScholarDigital Library
- Y. Rubner, C. Tomasi, and L. J. Guibas. A metric for distributions with applications to image databases. In Proceedings of the IEEE International Conference on Computer Vision, pages 59--66, 1998. Google ScholarDigital Library
- B. Sadeghi, V. Kanodia, A. Sabharwal, and E. Knightly. Oar: an opportunistic auto-rate media access protocol for ad hoc networks. Wirel. Netw., 11(1-2):39--53, 2005. Google ScholarDigital Library
- K. Srinivasan, P. Dutta, A. Tavakoli, and P. Levis. Some implications of low power wireless to ip networking. In The Fifth Workshop on Hot Topics in Networks (HotNets-V), Nov. 2006.Google Scholar
- K. Srinivasan and P. Levis. Rssi is under appreciated. In Proceedings of the Third ACM Workshop on Embedded Networked Sensors (EmNets 2006), May 2006.Google Scholar
- The Institute of Electrical and Electronics Engineers, Inc. Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs), Oct. 2003.Google Scholar
- A. Woo and D. Culler. Evaluation of efficient link reliability estimators for low-power wireless networks. Technical report, UC-Berkeley, November 2003.Google Scholar
Index Terms
- The β-factor: measuring wireless link burstiness
Recommendations
An empirical study of low-power wireless
We present empirical measurements of the packet delivery performance of the latest sensor platforms: Micaz and Telos motes. In this article, we present observations that have implications to a set of common assumptions protocol designers make while ...
The κ factor: inferring protocol performance using inter-link reception correlation
MobiCom '10: Proceedings of the sixteenth annual international conference on Mobile computing and networkingThis paper explores metrics that capture to what degree packet reception on different links is correlated. Specifically, it explores metrics that shed light on when and why opportunistic routing and network coding protocols perform well (or badly). It ...
Surviving wi-fi interference in low power ZigBee networks
SenSys '10: Proceedings of the 8th ACM Conference on Embedded Networked Sensor SystemsFrequency overlap across wireless networks with different radio technologies can cause severe interference and reduce communication reliability. The circumstances are particularly unfavorable for ZigBee networks that share the 2.4 GHz ISM band with WiFi ...
Comments