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Performance Analysis of Routing Protocols for Wireless Sensor Networks for Disaster Management

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In this paper, we analyze the performance of level controlled and gossip based routing protocols. We then combine both and analyze the performance as level controlled gossiping in the context of the occurrence of an abnormal event like Tsunami. We summarize the analysis mechanisms used to predict tsunami and briefly discuss the results of this algorithm. Our simulation results show that the combination of level controlled gossip and pure gossip yields better results.
Keyword:Level controlled, Gossip, Routing protocols.
World is a ground for numerous disasters almost daily [9]. These mass destruction incidents irrespective of whether natural calamities or man-made catastrophes cause a huge loss of money, property and lives due to non-planning on the part of the governments and the management agencies. It is therefore required to take steps towards the prevention of these situations by predetermining the causes of these disasters and providing quick rescue measures once the disaster occurs. Wireless Ad hoc sensor networks are playing a vital role in wireless data transmission infrastructure and can be very helpful in these situations. Technologies which can cause an alert for the immediate rescue operation to begin when disaster happens can be utilized by Wireless sensor networks. The wounds of the survivors who lost their near and dear ones in 2004 Tsunami are still fresh which ravaged the complete east coast of India. It is estimated that tens of thousands of people died in that event only in India and lakhs in other countries of Asia. Wireless sensor networks (WSNs) provide a simple, economic approach for the deployment of distributed monitor and control devices, avoiding the expensive retrofit necessary in wired systems [10].
A wireless sensor and actuator network is a collection of small randomly dispersed devices that provide three essential functions; the ability to monitor physical and environmental conditions, often in real time, such as temperature, pressure, light and humidity; the ability to operate devices such as switches, motors or actuators that control those conditions; and the ability to provide efficient, reliable communications.
The implementation of this last capability is the most unique to WSNs. Since they are designed for low traffic monitor and control applications, it is not necessary for them to support the high data throughput requirements that data networks like Wi-Fi require. Typical WSN over-the-air data rates range from 20 kbps to 1 Mbps. Consequently they can operate with much lower power consumption, which in turn allows the nodes to be battery powered and physically small. WSNs are typically self-organizing and self-healing. Self-organizing networks allow a new node to automatically join the network without the need for manual intervention
Self-healing networks allow nodes to reconfigure their link associations and find alternative pathways around failed or powered-down nodes. How these capabilities are implemented is specific to the network management protocol and the network topology, and ultimately will determine the network’s flexibility.
A routing protocol specifies how routers communicate with each other, disseminating information that enables them to select routes between any two nodes on a computer network. Routing algorithms determine the specific choice of route. Each router has a priori knowledge only of networks attached to it directly. A routing protocol shares this information first among immediate neighbors, and then throughout the network. This way, routers gain knowledge of the topology of the network.
The specific characteristics of routing protocols include the manner in which they avoid routing loops, the manner in which they select preferred routes, using information about hop costs, the time they require to reach routing convergence, their scalability, and other factors.


  1. Arora, Shashank, M. B. Srninvas, G. Ramamurthy, “Power Aware, Probabilistic and Adaptable Routing Algorithm for Wireless Sensor Networks”, National Conference on Communications (NCC 2004), IISc, Bangalore, pp. 60-64.
  2. K. Casey, A. Lim, and G. Dozier, “Evolving General Regression Neural Networks for Tsunami Detection and Response,” in Proceedings of the International Congress on Evolutionary Computation(CEC). IEEE, July 2006.
  3. Chenyang Lu, Brian M. Blum, Tarek F. Abdelzaher, John A. Stankovic, and Tian He, “ RAP: A Real-Time Communication Architecture for Large-Scale Wireless Sensor Networks,” IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2002) San Jose, CA, September 2002
  4. 5. X. -Y. Li, K. Moaveninejad and O. Frieder, “Regional Gossip Routing for Wireless Ad Hoc Networks, Mobile Networks And Applications (Monet), Vol. 10, No. 1-2, 2005, pp. 61-77
  5. Santosh Bhima, Anil Gogada and Ramamurthy Gaarimella, “Level Controlled Gossip based Tsunami Warning Wireless Sensor Networks”, Sensors & Transducers Journal, Vol. 106, Issue 7, July 2009, pp. 27-34
  6. Donald F. Specht, “A General Regression Neural Network,” IEEE Transactions on Neural Networks, Vol.2, No. 6, 1991.
  7. Zygmunt J. Haas, Joseph Y. Halpern, And Li (Erran), Gossip-Based Ad Hoc Routing, IEEE/ACM Transactions on Networking, Vol. 14, No. 3, June 2006.
  8. Aziz N.A.A., “Managing disaster with wireless sensor networks”, 13th International Conference on Advanced Communication Technology (ICACT), 2011, pp. 202 – 207
  9. Naveed Ahmad, Naveed Riaz, Mureed Hussain.”Ad hoc wireless Sensor Network Architecture for Disaster Survivor Detection”, International Journal of Advanced Science and Technology Vol. 34, September, 2011
  10. Harminder Kaur, Ravinder Singh Sawhney, Navita Komal, “Wireless Sensor Networks for Disaster Management”, International Journal of Advanced Research in Computer Engineering & Technology, Volume 1, Issue 5, July 2012