Vol.41, No.1, 2022, pp.67-82, doi:10.32604/csse.2022.018867
Cost Optimized Switching of Routing Protocol Scheme for IoT Applications
  • Karunanithi Praveen kumar, Perumal Sivanesan*
School of Computing, SASTRA University, Thanjavur, 613401, Tamilnadu, India
* Corresponding Author: Perumal Sivanesan. Email:
Received 24 March 2021; Accepted 09 May 2021; Issue published 08 October 2021
In this work, we propose a context-aware switching of routing protocol scheme for specific application requirements of IoT in real-time using a software-defined networking controller in wireless sensor networks. The work planned has two stages i) Selection of suitable routing protocol (RP) for given IoT applications using higher cognitive process and ii) Deployment of the corresponding routing protocol. We use the supervised learning-regression method for classification of the routing protocol while considering the network parameters like stability, path delay, energy utilization, and throughput. The chosen routing protocol will be set in the sensor network using a software-defined networking controller in an exceedingly flexible manner during the second stage. Extensive simulation has been done and results are evaluated to point out the strength of the proposed work, while dynamically varying the specific requirements of IoT applications. We observe that the work proposed is path-breaking the prevailing methods, where a specific routing protocol is employed throughout the period of time. It’s clearly shown that the proposed, Low-cost Context-Aware Protocol Switching (LCAPS) scheme is efficient in improving the performance of the sensor network and also meets the specific application requirements of IoT by using Software-Defined Wireless Sensor Networks SDWSNs.
Internet of things; sensor network efficiency; software-defined networking; wireless sensor networks; supervised learning; cost optimization
Cite This Article
Kumar, K. P., Sivanesan, P. (2022). Cost Optimized Switching of Routing Protocol Scheme for IoT Applications. Computer Systems Science and Engineering, 41(1), 67–82.
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