Research Article
CA-RPL: A Clustered Additive Approach in RPL for IoT Based Scalable Networks
@INPROCEEDINGS{10.1007/978-3-030-20615-4_8, author={Soumya Mishra and Suchismita Chinara}, title={CA-RPL: A Clustered Additive Approach in RPL for IoT Based Scalable Networks}, proceedings={Ubiquitous Communications and Network Computing. Second EAI International Conference, Bangalore, India, February 8--10, 2019, Proceedings}, proceedings_a={UBICNET}, year={2019}, month={5}, keywords={IoT RPL Cluster Additive}, doi={10.1007/978-3-030-20615-4_8} }- Soumya Mishra
Suchismita Chinara
Year: 2019
CA-RPL: A Clustered Additive Approach in RPL for IoT Based Scalable Networks
UBICNET
Springer
DOI: 10.1007/978-3-030-20615-4_8
Abstract
Applications of the Internet of Things (IoT) span from the industrial field to the agriculture field and from the smart city to the smart city healthcare. The wireless sensors play a major role in making these applications work as they are desired. These tiny, light-weight and low battery-powered sensors make the smallest of the smallest device communicate in an IoT environment. All of these applications require hundred to thousands of nodes to solve a purpose. Routing in such energy constrained network becomes a challenging task, so scalability in IoT is one of the major challenges that need to be solved. Routing protocol for low power and lossy networks (RPL) is one of the protocols developed by the Routing Over Low Power And Lossy Networks (ROLL) group to meet the QoS requirements for various IoT based applications. However, the existing versions of RPL fail to provide better results when the number of nodes in the network is increased. Our proposed protocol Clustered Additive RPL (CA-RPL) uses a weight based clustering technique to meet the efficiency of a scalable network. In addition to that, the path selection for data transmission is done by considering three parameters namely Expected transmission count (ETX), hop count and available energy. It is observed that the proposed approach outperforms other approaches in terms of packet delivery ratio, end to end delay and energy consumption in the network.