A Comparative Analysis of Important Energy Conservation Approaches in IoT

Sindhu, Ankita; Roy, Nihar Ranjan

doi:10.1109/confluence51648.2021.9377099

Cited by 2 publications

(1 citation statement)

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“…However, the problem with these battery-operated wireless sensor systems is that it would be physically impossible to replace the batteries of billions of devices spread over the globe, let alone space. Not only that, but the short lifespan of batteries would cause network operations to be disrupted [4]. Currently, the issue regarding energy in the Internet of Things (IoT) industry, IoT sensors with low energy consumption and long battery life are required, i.e., a sensor's battery must last 10 to 15 years [5].…”

Section: Introductionmentioning

confidence: 99%

CETS: Enabling Sustainable IoT with Cooperative Energy Transfer Schedule towards 6G Era

Kumar

Gopikrishnan

2022

Sensors

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The large scale of the Internet of Things necessitates using long-lasting physical layer devices for data collection. Deploying large numbers of Wi-Fi-enabled devices is expensive, so the Internet of Everything (IoE) is equipped with multiple communication modules to collect data where Wi-Fi is unavailable. However, because of their extended communication capabilities, IoE devices face energy limitations. As a result, IoE devices must be provided with the necessary energy resources. This paper introduces a novel multi-hop cooperation communication mechanism for Wireless Energy Transfer (WET) in the Wireless Powered-Internet of Everything (WP-IoE). IoE devices are outfitted here with various communication devices such as RF, Bluetooth, and Wi-Fi. This research proposes a two-phase energy transmission schedule to address the energy requirements. For data collection, the first phase provides a distributed tree-based data communication plan. The proposed model’s second phase used the reverse data collection protocol to implement wireless energy transmission. By combining these two phases, an optimized WET framework was created without unmanned aerial vehicles or robots. The experimental findings show that the proposed method in this research increases the average lifetime of the network and has a more significant charge latency and average charge throughput than other models.

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Section: Introductionmentioning

confidence: 99%