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http://dx.doi.org/10.3837/tiis.2022.06.005

A Novel Duty Cycle Based Cross Layer Model for Energy Efficient Routing in IWSN Based IoT Application  

Singh, Ghanshyam (Electronics and Communication Department, National Institute of Technology)
Joshi, Pallavi (Electronics and Communication Department, National Institute of Technology)
Raghuvanshi, Ajay Singh (Electronics and Communication Department, National Institute of Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.16, no.6, 2022 , pp. 1849-1876 More about this Journal
Abstract
Wireless Sensor Network (WSN) is considered as an integral part of the Internet of Things (IoT) for collecting real-time data from the site having many applications in industry 4.0 and smart cities. The task of nodes is to sense the environment and send the relevant information over the internet. Though this task seems very straightforward but it is vulnerable to certain issues like energy consumption, delay, throughput, etc. To efficiently address these issues, this work develops a cross-layer model for the optimization between MAC and the Network layer of the OSI model for WSN. A high value of duty cycle for nodes is selected to control the delay and further enhances data transmission reliability. A node measurement prediction system based on the Kalman filter has been introduced, which uses the constraint based on covariance value to decide the scheduling scheme of the nodes. The concept of duty cycle for node scheduling is employed with a greedy data forwarding scheme. The proposed Duty Cycle-based Greedy Routing (DCGR) scheme aims to minimize the hop count, thereby mitigating the energy consumption rate. The proposed algorithm is tested using a real-world wastewater treatment dataset. The proposed method marks an 87.5% increase in the energy efficiency and reduction in the network latency by 61% when validated with other similar pre-existing schemes.
Keywords
Cross-layer optimization; Duty cycle; Greedy routing; Kalman filter; Node scheduling;
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