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Title	Energy Optimized Route Selection In Wsns For Smart Iot Applications
ID_Doc	23355
Authors	Poongodi T.; Sharma R.K.
Year	2023
Published	2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023
DOI	http://dx.doi.org/10.1109/ICDCECE57866.2023.10150824
Abstract	Interest in the IoT and smart cities has been growing as people learn about its potential applications in fields as diverse as healthcare, remote monitoring, and transportation. In these Internet of Things (IoT)-based systems, wireless networked sensors (WSNs) gather data critical to the operation of smart surroundings. IoT-enabled WSNs face challenges such high latency, low bandwidth, and short network lifespan due to the copious amounts of data generated by a wide variety of sensors. This study presents a deep reinforcement learning-based efficient routing method for IoT-enabled WSNs to combat latency as well as electricity consumption (DRL). The proposed strategy separates the network into unequal cluster according to the present data transmission existing in the sensors, hence preventing the network from collapsing prematurely. Extensive testing has been performed in ns3 using the recommended strategy. The results of the experiments are contrasted to the state-of-the-art methodologies to demonstrate that the proposed method is effective in the areas in received packets, connectivity latency, clean energy, and the amount of living nodes within a network. © 2023 IEEE.
Author Keywords	Energy Efficiency; Routing; Wireless Sensor Networks and Smart IoT Applications

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