The Community for Technology Leaders
RSS Icon
Issue No.06 - June (2008 vol.7)
pp: 682-697
Data generated in wireless sensor networks may not all be alike; some data may be more important than others and hence may have different delivery requirements. In this paper we address differentiated data delivery in the presence of congestion in wireless sensor networks. We propose a class of algorithms that enforce differentiated routing based on the congested areas of a network and data priority. The basic protocol, called Congestion Aware Routing (CAR), discovers the congested zone of the network that exists between high priority data sources and the data sink, and using simple forwarding rules dedicates this portion of the network to forwarding primarily high priority traffic. Since CAR requires some overhead for establishing the high priority routing zone, it is unsuitable for highly mobile data sources. To accommodate these we define MAC-enhanced Congestion Aware Routing (MCAR), which includes MAC-layer enhancements and a protocol for forming high priority paths on the fly for each burst of data. MCAR effectively handles mobility of high priority data sources at the expense of degrading the performance of low priority traffic. We present extensive simulation results for CAR and MCAR, and an implementation of MCAR on a 48 node testbed.
Wireless communication, Routing protocols, Wireless Sensor Networks, Congestion
Riccardo Crepaldi, Raju Kumar, Albert F. Harris III, Guohong Cao, Michele Zorzi, Thomas F. La Porta, "Mitigating Performance Degradation in Congested Sensor Networks", IEEE Transactions on Mobile Computing, vol.7, no. 6, pp. 682-697, June 2008, doi:10.1109/TMC.2008.20
[1] Draft Supplement to Part 11: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Medium Access Control (MAC) Enhancements for Quality of Service (QoS), IEEE 802.11e/D4.0, Nov. 2002.
[2] G.-S. Ahn, S.G. Hong, E. Miluzzo, A.T. Campbell, and F. Cuomo, “Funneling-MAC: A Localized, Sink-Oriented MAC for Boosting Fidelity in Sensor Networks,” Proc. Fourth ACM Conf. Embedded Networked Sensor Systems (SenSys), 2006.
[3] G.-S. Ahn, L.-H. Sun, A. Veres, and A.T. Campbell, “Swan: Service Differentiation in Stateless Wireless Ad Hoc Networks,” Proc. IEEE INFOCOM, 2002.
[4] K. Akkaya and M.F. Younis, “An Energy-Aware QoS Routing Protocol for Wireless Sensor Networks,” Proc. 23rd IEEE Int'l Conf. Distributed Computing Systems (ICDCS '03), pp. 710-715, 2003.
[5] S.R. Das, C.E. Perkins, and E.M. Belding-Royer, “Performance Comparison of Two On-Demand Routing Protocols for Ad Hoc Networks,” Proc. IEEE INFOCOM '00, pp. 3-12, 2000.
[6] C.T. Ee and R. Bajcsy, “Congestion Control and Fairness for Many-to-One Routing in Sensor Networks,” Proc. Second ACM Conf. Embedded Networked Sensor Systems (SenSys '04), pp. 148-161, 2004.
[7] E. Felemban, C.-G. Lee, and E. Ekici, “MMSPEED: Multipath Multi-SPEED Protocol for QoS Guarantee of Reliability and Timeliness in Wireless Sensor Networks,” IEEE Trans. Mobile Computing, vol. 6, pp. 738-754, 2006.
[8] T. He, J.A. Stankovic, C. Lu, and T. Abdelzaher, “Speed: AStateless Protocol for Real-Time Communication in Sensor Networks,” Proc. 23rd IEEE Int'l Conf. Distributed Computing Systems (ICDCS), 2003.
[9] J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. Culler, and K. Pister, “System Architecture Directions for Network Sensors,” Proc. Ninth Int'l Conf. Architectural Support for Programming Languages and Operating Systems (ASPLOS '00), Nov. 2000.
[10] B. Hull, K. Jamieson, and H. Balakrishnan, “Mitigating Congestion in Wireless Sensor Networks,” Proc. Second ACM Conf. Embedded Networked Sensor Systems (SenSys), 2004.
[11] Eyesifxv2 Version 2.0. Infineon, http:/, 2008.
[12] C. Intanagonwiwat, R. Govindan, and D. Estrin, “Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks,” Proc. ACM MobiCom '00, Aug. 2000.
[13] D.B. Johnson and D.A. Maltz, “Dynamic Source Routing in AdHoc Wireless Networks,” Mobile Computing, pp. 153-181, Kluwer Academic Publishers, Feb. 1996.
[14] B. Karp and H. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks,” Proc. ACM MobiCom, 2000.
[15] C. Lu, B. Blum, T. Abdelzaher, J. Stankovic, and T. He, “RAP: A Real-Time Communication Architecture for Large-Scale Wireless Sensor Networks,” Proc. Eighth IEEE Real-Time and Embedded Technology and Applications Symp. (RTAS '02), pp. 55-66, 2002.
[16] S. Madden, M. Franklin, J. Hellerstein, and W. Hong, “Tag: A Tiny Aggregation Service for Ad-Hoc Sensor Networks,” Proc. FifthSymp. Operating System Design and Implementation (OSDI), 2002.
[17] ns2: Network Simulator,, 2008.
[18] C.E. Perkins and E.M. Royer, “Ad Hoc On-Demand Distance Vector Routing,” Proc. Second IEEE Workshop Mobile Computing Systems and Applications (WMCSA '99), Feb. 1999.
[19] J. Polastre, J. Hill, and D. Culler, “Versatile Low Power Media Access for Wireless Sensor Networks,” Proc. Second ACM Conf. Embedded Networked Sensor Systems (SenSys), 2004.
[20] S. Rangwala, R. Gummadi, R. Govindan, and K. Psounis, “Interference-Aware Fair Rate Control in Wireless Sensor Networks,” Proc. ACM SIGCOMM, 2006.
[21] N. Shrivastava, C. Buragohain, D. Agrawal, and S. Suri, “Medians and Beyond: New Aggregation Techniques for Sensor Networks,” Proc. Second ACM Conf. Embedded Networked Sensor Systems (SenSys), 2004.
[22] C.-Y. Wan, S.B. Eisenman, and A.T. Campbell, “CODA: Congestion Detection and Avoidance in Sensor Networks,” Proc. FirstACM Conf. Embedded Networked Sensor Systems (SenSys '03), pp.266-279, 2003.
[23] A. Woo and D.E. Culler, “A Transmission Control Scheme for Media Access in Sensor Networks,” Proc. ACM MobiCom, 2001.
[24] W. Ye, J. Heidemann, and D. Estrin, “An Energy-Efficient MAC Protocol for Wireless Sensor Networks,” Proc. IEEE INFOCOM, 2002.
[25] H. Zhang, A. Arora, Y. Choi, and M. Gouda, “Reliable Bursty Convergecast in Wireless Sensor Networks,” Proc. ACM MobiHoc, 2005.
[26] Y. Zhang, M.P.J. Fromherz, and L.D. Kuhn, “Smart Routing with Learning-Based QoS-Aware Meta-Strategies,” Proc. First Workshop Quality of Service Routing (WQoSR '04), pp. 298-307, 2004.
34 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool