Distributed energy-efficient wireless sensing and information fusion via event-driven and state-rank activation

Fu, Juteng; Ma, Xiang; Yu, Hang; Dai, Keren

doi:10.1007/s11276-024-03691-8

Cited by 4 publications

(1 citation statement)

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“…Thus, energy efficiency is a key aspect and the subject of research in wireless sensor networks. The authors of [ 17 ] proposed a cascaded sensor dynamic activation and information fusion advanced mechanism which significantly improved the energy utilization efficiency and sensing performance of wireless sensor networks and has great potential for application.…”

Section: Literature Reviewmentioning

confidence: 99%

A Nature-Inspired Approach to Energy-Efficient Relay Selection in Low-Power Wide-Area Networks (LPWAN)

Strzoda,

Grochla

2024

Sensors

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Despite the ability of Low-Power Wide-Area Networks to offer extended range, they encounter challenges with coverage blind spots in the network. This article proposes an innovative energy-efficient and nature-inspired relay selection algorithm for LoRa-based LPWAN networks, serving as a solution for challenges related to poor signal range in areas with limited coverage. A swarm behavior-inspired approach is utilized to select the relays’ localization in the network, providing network energy efficiency and radio signal extension. These relays help to bridge communication gaps, significantly reducing the impact of coverage blind spots by forwarding signals from devices with poor direct connectivity with the gateway. The proposed algorithm considers critical factors for the LoRa standard, such as the Spreading Factor and device energy budget analysis. Simulation experiments validate the proposed scheme’s effectiveness in terms of energy efficiency under diverse multi-gateway (up to six gateways) network topology scenarios involving thousands of devices (1000–1500). Specifically, it is verified that the proposed approach outperforms a reference method in preventing battery depletion of the relays, which is vital for battery-powered IoT devices. Furthermore, the proposed heuristic method achieves over twice the speed of the exact method for some large-scale problems, with a negligible accuracy loss of less than 2%.

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Section: Literature Reviewmentioning

confidence: 99%