Performance Tradeoff with Routing Protocols for Radio Models in Wireless Sensor Networks

DOI: 10.4236/wet.2011.22008   PDF   HTML     5,403 Downloads   10,597 Views   Citations


In this paper, we have simulated and evaluated the performance tradeoff with routing protocols: Constrained Flooding, the Real-Time Search and the Adaptive Tree on MICA and MICAz platform with different radio models using PROWLER for wireless sensor networks. The simulation results establish that the MICAz motes give low latency, high throughput, high energy consumption, low efficiency but better lifetime while the MICA motes give high success rate and less loss rate. It has been, thus, concluded that in case of all the radio models the MICAz is preferably better than MICA in applications where energy is a constraint. Moreover, use of MICAz motes increases the network lifetime in comparison to MICA for the radio models. Further, the AT protocol can be applied to achieve better energy consumption, efficiency and lifetime in real time for wireless sensor networks.

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M. Bala and L. Awasthi, "Performance Tradeoff with Routing Protocols for Radio Models in Wireless Sensor Networks," Wireless Engineering and Technology, Vol. 2 No. 2, 2011, pp. 53-59. doi: 10.4236/wet.2011.22008.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] J. N. Al-Karaki and A. E. Kamal, “A Taxonomy of Routing Techniques in Wireless Sensor Networks,” In M. Ilyas and I. Mahgoub, Eds., Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems, Chapter 6, CRC Press, Boca Raton, 2005, pp. 1-24.
[2] B. Karp and H. T. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks,” Proceedings of 6th International Conference on Mobile Computing and Networks, Boston, 6-11 August 2000, pp. 243-254. doi:10.1145/345910.345953
[3] M. Chu, H. Haussecker and F. Zhao, “Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks,” International Journal of High Performance Computing Applications, Vol. 16, No. 3, 2002, pp. 293-313. doi:10.1177/10943420020160030901
[4] Y. Yu, R. Govindan and D. Estrin, “Geographical and Energy Aware Routing: A Recursive Data Dissemination Protocol for Wireless Sensor Networks,” Technical Report UCLA/CSD-TR-01-0023, Computer Science Depart- ment, University of California, Los Angeles, May 2001.
[5] Y. Zhang and M. P. J. Fromherz, “Message-Initiated Constraint-Based Routing for Wireless Ad-Hoc Sensor Networks,” Proceedings of 1st IEEE Consumer Communication and Networking Conference, Las Vegas, 5-8 January 2004, pp. 648-650.
[6] Y. Zhang, M. P. J. Fromherz and L. D. Kuhn, “Smart Routing with Learning-Based QoS-Aware Meta-Strategies,” Proceedings of 1st Workshop Quality of Service Routing, Barcelona, 1 October 2004, pp. 298-307.
[7] Y. Zhang and M. Fromherz, “Search-Based Adaptive Routing Strategies for Sensor Networks,” Proceedings of AAAI Sensor Networks Workshop, San Jose, 26 July 2004, pp. 1-8.
[8] Y. Zhang and M. P. J. Fromherz, “Constrained Flooding: A Robust and Efficient Routing Framework for Wireless Sensor Networks,” Proceedings of 20th IEEE International Conference on Advanced Information Networking and Applications, Vienna, 18-20 April 2006, pp. 1-6.
[9] Y. Zhang and Q. F. Huang, “Adaptive Tree: A Learning- Based Meta-Routing Strategy for Sensor Networks,” Pro- ceedings of 3rd IEEE Consumer Communications and Networking Conference, 8-10 January 2006, pp. 122-126.
[10] Y. Zhang, G. Simon and G. Balogh, “High-Level Sensor Network Simulations for Routing Performance Evaluations,” Proceedings of 3rd International Conference on Networked Sensing Systems, Chicago, 31 May-2 June 2006, pp. 1-4.
[11] S. Park, A. Savvides and M. B. Srivastava, “SensorSim: A Simulation Framework for Sensor Networks,” Proceedings of the 3rd ACM International Workshop on Modeling, Analysis and Simulation of Wireless and Mobile Systems, Boston, 20 August 2000, pp. 104-111.
[12] P. Levis, N. Lee, M. Welsh and D. Culler, “TOSSIM: Accurate and Scalable Simulation of Entire TinyOS Applications,” Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, Los Angeles, 5-7 November 2003, pp. 126-137. doi:10.1145/958491.958506
[13] K. Fall and K. Varadhan, “The VINT Project,” The NS Manual, November 2008.
[14] OPNET Technologies, Inc., “The OPNET Simulator,” Bethesda.
[15] G. Simon, “Prowler: Probabilistic Wireless Network Simulator,” Institute for Software Integrated Systems, Nashville, 2003.
[16] G. Simon, P. Volgyesi, M. Maroti and A. Ledeczi, “Si- mulation-Based Optimization of Communication Protocols for Large-Scale Wireless Sensor Networks,” Procee- dings of IEEE International Aerospace Conference, Big Sky, Vol. 3, 8-15 March 2003, pp. 1339-1346.
[17] M. Haenggi, “Probabilistic Analysis of a Simple Mac Scheme for Ad Hoc Wireless Networks,” Proceedings of IEEE CAS Workshop on Wireless Communications and Networking, Pasadena, 5-6 September 2002, pp. 1-4.
[18] U. C. Berkeley Wireless Embedded Systems, 2003.
[19] Y. Zhang and M. Fromherz, “A Robust and Efficient Flooding-Based Routing for Wireless Sensor Networks,” Journal of Interconnection Networks, Vol. 7, No. 4, 2006, pp. 549-568. doi:10.1142/S0219265906001855
[20] Crossbow: MICA, Wireless Measurement System Datasheet.
[21] Crossbow: MICAz, Wireless Measurement System Datasheet.

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