Bernhard Firner
ABSTRACT
A typical wireless sensor network consists of many small sensors that collect instrument data around their locations and forward it to a central location for data processing. These networks can be deployed to monitor livestock and agricultural assets, products in a store, patients in a hospital, and so on. In many cases sensors have to be densely deployed, and collisions or overhead due to collision avoidance will considerably degrade the system performance below an application's required levels. With the decreasing cost of radio devices the obvious solution to this problem is the use of multiple receivers on different radio channels. However, we show that if receivers can be placed in different locations then increasing the number of receivers on a single channel will increase the rate of the capture effect and decrease collision losses, while also increasing the fairness of the transmitters' radio links. Not only can this single channel approach be more effective than using multiple channels, it is also required for some techniques, such as localization, where each receiver must be able to detect a transmission from any transmitter. We also show that the optimal choice between these two solutions is influenced by the radio attenuation rate and the number of receivers in the system.
- }}Junaid Ansari, Xi Zhang, and Petri Mähönen. Multi-radio medium access control protocol for wireless sensor networks. In SenSys '07: Proceedings of the 5th international conference on Embedded networked sensor systems, pages 403--404, New York, NY, USA. 2007. ACM. Google Scholar
Digital Library
- }}Anish Arora, Rajiv Ramnath, Emre Ertin, Prasun Sinha, Sandip Bapat, Vinayak Naik, Vinod Kulathumani, Hongwei Zhang, Hui Cao, Mukundan Sridharan, Santosh Kumar, Nick Seddon, Chris Anderson, Ted Herman, Nishank Trivedi, Chen Zhang, Mikhail Nesterenko, Romil Shah, Sandeep Kulkarni, Mahesh Aramugam, Limin Wang, Mohamed Gouda, Young-ri Choi, David Culler, Prabal Dutta, Cory Sharp, Gilman Tolle, Mike Grimmer, Bill Ferriera, and Ken Parker. Exscal: Elements of an extreme scale wireless sensor network. In RTCSA '05: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, pages 102--108, Washington, DC, USA, 2005. IEEE Computer Society. Google ScholarDigital Library
- }}Xun Chen, Peng Han, Qiu-Sheng He, Shi-liang Tu, and Zhang-Long Chen. A multi-channel mac protocol for wireless sensor networks. In CIT '06: Proceedings of the Sixth IEEE International Conference on Computer and Information Technology, page 224, Washington, DC, USA, 2006. IEEE Computer Society.Google ScholarDigital Library
- }}Yingying Chen, J.-A. Francisco, W. Trappe, and R.P. Martin. A practical approach to landmark deployment for indoor localization. In Sensor and Ad Hoc Communications and Networks, 2006. SECON '06. 2006 3rd Annual IEEE Communications Society on, volume 1, pages 365--373, Sept. 2006.Google ScholarCross Ref
- }}Henri Dubois-Ferrière, Deborah Estrin, and Martin Vetterli. Packet combining in sensor networks. In SenSys '05: Proceedings of the 3rd international conference on Embedded networked sensor systems, pages 102--115, New York, NY, USA. 2005. ACM. Google ScholarDigital Library
- }}Bernhard Firner, Prashant Jadhav, Yanyong Zhang, Richard Howard, Wade Trappe, and Eitan Fenson. Towards continuous asset tracking: Low-power communication and fail-safe presence assurance. In Sensor, Mesh and Ad Hoc Communications and Networks, 2009. SECON '09. 6th Annual IEEE Communications Society Conference on, pages 1--9. June 2009. Google ScholarDigital Library
- }}Bernhard Firner, Shweta Medhekar, Yanyong Zhang, Richard Howard, Wade Trappe, Peter Wolniansky, and Eitan Fenson. PIP Tags: Hardware Design and Power Optimization. In Proceedings of the Fifth Workshop on Embedded Networked Sensors (HotEmNets), June 2008.Google Scholar
- }}Gregory Hackmann, Octav Chipara, and Chenyang Lu. Robust topology control for indoor wireless sensor networks. In SenSys '08: Proceedings of the 6th ACM conference on Embedded network sensor systems, pages 57--70, New York, NY, USA, 2008. ACM. Google ScholarDigital Library
- }}G. P. Halkes1 and K. G. Langendoen. Crankshaft: An energy-efficient mac-protocol for dense wireless sensor networks. In EWSN 2007, pages 228--244, January 2007. Google ScholarDigital Library
- }}Wendi Rabiner Heinzelman, Anantha Ch, and Hari Balakrishnan. Energy-efficient communication protocol for wireless microsensor networks pages 3005--3014, 2000.Google Scholar
- }}Ozlem Durmaz Incel, Stefan Dulman, and Pierre Jansen. Multi-channel support for dense wireless sensor networking. In Smart Sensing and Context, EuroSSC 2006, pages 1--14. October 2006. Google ScholarDigital Library
- }}Youngmin Kim, Hyojeong Shin, and Hojung Cha. Y-mac: An energy-efficient multi-channel mac protocol for dense wireless sensor networks. In IPSN '08: Proceedings of the 7th international conference on Information processing in sensor networks, pages 53--63, Washington, DC, USA, 2008. IEEE Computer Society. Google ScholarDigital Library
- }}Jeongkeun Lee, Wonho Kim, Sung-Ju Lee, Daehyung Jo, Jiho Ryu, Taekyoung Kwon, and Yanghee Choi. An experimental study on the capture effect in 802.11a networks. In WinTECH '07: Proceedings of the second ACM international workshop on Wireless network testbeds, experimental evaluation and characterization, pages 19--26, New York, NY, USA, 2007. ACM. Google ScholarDigital Library
- }}Young ri Choi, Mohamed G. Gouda, Hongwei Zhang, and Anish Arora. Routing on a logical grid in sensor networks. Technical report, 2004.Google Scholar
- }}N. K. Santhapuri, J. Manweiler, S. Sen, R. R. Choudhury, S. Nelakuditi, and K. Munagala. Message in message mim: A case for reordering transmissions in wireless networks. In HotNets VII, 2008.Google Scholar
- }}Dongjin Son, Bhaskar Krishnamachari, and John Heidemann. Experimental study of concurrent transmission in wireless sensor networks. In SenSys '06: Proceedings of the 4th international conference on Embedded networked sensor systems, pages 237--250, New York, NY, USA. 2006. ACM. Google ScholarDigital Library
- }}Texas Instruments Norway AS. CC1100 Single Chip Low Cost Low Power RF Transceiver, June 2006. Data Sheet (Rev.1.1).Google Scholar
- }}T. Wark, P. Corke, P. Sikka, L. Klingbeil, Ying Guo, C. Crossman, P. Valencia, D. Swain, and G. Bishop-Hurley. Transforming agriculture through pervasive wireless sensor networks. Pervasive Computing, IEEE, 6(2):50--57, April-June 2007. Google ScholarDigital Library
- }}Tim Wark, Chris Crossman, Wen Hu, Ying Guo, Philip Valencia, Pavan Sikka, Peter Corke, Caroline Lee, John Henshall, Kishore Prayaga, Julian O'Grady, Matt Reed, and Andrew Fisher. The design and evaluation of a mobile sensor/actuator network for autonomous animal control. In IPSN '07: Proceedings of the 6th international conference on Information processing in sensor networks, pages 206--215, New York, NY, USA, 2007. ACM. Google ScholarDigital Library
- }}J. Wilson and N. Patwari. Radio tomographic imaging with wireless networks. Mobile Computing, IEEE Transactions on, 2009. Accepted for future publication. Google ScholarDigital Library
- }}Hongwei Zhang, Anish Arora, Young-ri Choi, and Mohamed G. Gouda. Reliable bursty convergecast in wireless sensor networks. In MobiHoc '05: Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing, pages 266--276, New York, NY, USA, 2005. ACM. Google ScholarDigital Library
Index Terms
- Multiple receiver strategies for minimizing packet loss in dense sensor networks
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