A wireless sensor network is made up of a large number of sensor nodes deployed on a wide field and it has limited battery lifetime which gets depleted at a faster rate, when heavy data traffic occurs. Most recent researches focused that, clustering the group of nodes is a better strategy for enhancing the lifetime of the sensors and also clustering organizes the network by balancing the traffic load of the sensor nodes. Inspired by the benefits of clustering approach, Event Based Routing Protocol (EBRP) was proposed. The proposed protocol involves three procedures. First procedure refers to a cluster head selection, which appoints cluster head based upon residual energy which is near to the sink node. The residual nodes in the network are to be designated as cluster head at the successive rounds. This process helps to balance the load evenly in the network. Second phase refers to an Event sensing procedure, which appoints a set of active nodes for close sensing an event and to provide coverage area near to the event. Third step refers to a node routing, to route the witnessed information based upon the shortest path. This proposed method uses residual energy for appointing a cluster head. This proposed protocol was implemented and the experimental results were shown through the network simulator. The proposed protocol outperforms the existing routing techniques in terms of alive nodes, packet delivery ratio, average remaining energy and end-to-end delay.
Clustering, Energy efficiency, Event sensing, Residual energy
 Z. Liu, Q. Zheng, L. Xue, X. Guan, (2012). A distributed energy-efficient clustering algorithm with improved coverage in wireless sensor networks. Future Generation Computer System, 28, 780–790.
 S. Bhattacharjee, S. Bandyopadhyay, (2013). Lifetime maximizing dynamic energy efficient routing protocol for multihop wireless networks. Simulation Modelling Practice and Theory, 32, 15–29.
 C. Lin, G. Wu, F. Xia, M. Li, L. Yao, Z. Pei, (2012). Energy efficient ant colony algorithms for data aggregation in wireless sensor networks. Journal of Computer and System Sciences, 78, 1686–1702.
 M. Azharuddin, P. Kuila, P.K. Jana (2015). Energy efficient fault tolerant clustering and routing algorithms for wireless sensor networks. Computers & Electrical Engineering, 41, 177-190.
 T., Liu, Q. Li, P. Liang. (2012). An energy-balancing clustering approach for gradient-based routing in wireless sensor networks. Computer Communication, 35, 2150–2161.
 P. Kuila, P.K. Jana (2014). A novel differential evolution based clustering algorithm for wireless sensor networks. Applied Soft Computing, 25, 414–425.
 S. Hu, J. Han, X. Wei, Z. Chen (2015). A multi-hop heterogeneous cluster-based optimization algorithm for wireless sensor networks. Wireless Networks, 21, 57–65.
 L. Shi, B., Zhang, H.T. Mouftah, J. Ma. (2013). DDRP: An efficient data-driven routing protocol for wireless sensor networks with mobile sinks. International Journal of Communication Systems, 26, 1341–1355.
 Agarwal D., N. Kishor, (2014). Network lifetime enhanced tri-level clustering and routing protocol for monitoring of offshore wind farms. IET Wireless Sensor Systems, 4, 69–79.
 M. Faheem, B. Asri, S. Ali, M. Shahid, L. Sakar. (2013). Energy based efficiency evaluation of cluster-based routing protocols for wireless sensor networks (WSNs). International Journal of Software Engineering and Its Applications, 7, 249–264.
 D. Gong, Y. Yang, Z. Pan, (2013). Energy-efficient clustering in lossy wireless sensor networks. Journal of Parallel and Distributed Computing, 73, 1323–1336.
 M. Soleimani, M. Ghasemzadeh, M.A. Sarram, (2011). A new cluster based routing protocol for prolonging network lifetime in wireless sensor networks. Middle-East Journal of Scientific Research, 7, 884–890.
 K.S. Zhang, L. Zhong, L. Tian, X.Y. Zhang, L. Li (2017). DBIECM-an Evolving Clustering Method for Streaming Data Clustering. AMSE journals; Advances B (Signal Processing and Pattern Recognition, Vol. 60; N°1; pp 239-254.
 H. Kim, J. Kim, (2015). An Energy-Efficient Balancing Scheme in wireless sensor networks. Wireless Personal Communications, 1-13.
 B. Wang, , H.B. Lim, D. Ma, (2012). A Coverage aware clustering protocol for wireless sensor networks. Computer Networks, 56, 1599-1611.
 L. Almazaydeh, E. Abdelfattah, M. Al-Bzoor, A. Al-Rahayfeh. (2010). Performance evaluation of routing protocols in wireless sensor networks. Computer Science and Information Technology, 2(2), 64–73.
 W.B. Heinzelman , A. Chandrakasan , H. Balakrishnan (2000). Energy-efficient communication protocol for wireless microsensor networks. Proceedings of the 33rd Hawaii International Conference on System Sciences.
 N. Shanthi, L. Ganesan, K. Ramar (2010). Secure multicast route path formation in Adhoc on-demand distance vector protocol. AMSE journals; Advances D (Computer Science and Statistics), Vol. 15; Nº 1-2, issue 1, pp 30-44.
 S. Deng, J. Li, L. Shen (2011). Mobility based clustering protocol for wireless sensor network with mobile nodes. IET Wireless sensor systems, 1(1), 39-47.
 S. Sivakumar, R. Venkatesan (2014). Cuckoo Search with Mobile Anchor Positioning (CS-MAP) Algorithm for Error Minimization in Wireless Sensor Networks. AMSE journals; Advances D, vol. 19 Nº 1, issue 1, pp 33-  The Network Simulator ns2. http://www.isi.edu/nsnam/ns/.