Publication Type : Conference Proceedings
Publisher : 6th International Conference on Advances in Computing, Communications Informatics
Source : 6th International Conference on Advances in Computing, Communications & Informatics (ICACCI’17), IEEE, Manipal University, Karnataka (2017)
Url : http://ieeexplore.ieee.org/document/8126141/
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2017
Abstract : Wireless sensor networks (WSN) are widely used various applications such as disaster management, search and rescue operation, wild life monitoring, remote patient monitoring, structural health monitoring etc. It provides bridge between the real physical and virtual worlds. In many scenarios, the coverage area of the WSN will be very large and a multi-hop adhoc network needs to be maintained for the connectivity and data transfer among the nodes. The major part of the energy consumption of each node is used for data transfer among nodes. This paper proposes a energy efficient routing scheme. The scenario which is considered is a wireless sensor network which is a collection of clusters and data transfer happens with the help of cluster head (CH) rather than the collective effort of every node in the network. In such a cluster based WSN, it is advantageous to have a routing protocol which uses the information about clusters to decide upon route formation. This paper proposes a novel Cluster Based Routing Protocol for a WSN which optimizes the energy consumption on data transfer and thus increasing the lifetime of the WSN network. To conclude the advantages of the proposed scheme, comparison is carried out between the performance of AODV and CBRP protocols.
Cite this Research Publication : B. Sreevidya and Rajesh M, “Enhanced Energy Optimized Cluster Based On Demand Routing Protocol for Wireless Sensor Networks ”, in 6th International Conference on Advances in Computing, Communications & Informatics (ICACCI’17), Manipal University, Karnataka , 2017.