Dynamic sink movement strategy for expedited query processing in Internet of things-based sensor networks DOI Creative Commons

Dongliang Xu

Journal of Engineering and Applied Science, Journal Year: 2025, Volume and Issue: 72(1)

Published: March 29, 2025

Abstract Wireless sensor networks (WSNs) represent an essential infrastructure that supports the Internet of things (IoT) and enables intelligent data collection from various contexts. In IoT-driven systems, nodes collect real-time data, initiate end-user or application requests, forward gathered to a cloud server. Query processing in WSN aims obtain accurate while conserving network resources. However, traditional static sink-based query methods often face challenges related lifetime lengthy delays. To mitigate these drawbacks, this paper proposes novel dynamic strategy (DSQPS) for IoT-enabled WSNs. DSQPS first calculates optimum number rendezvous points on by solving minimal set covering problem, followed Aquila Optimizer (AO), which optimizes mobile sinks. addition, optimized movement path sinks is determined, minimizing delays processing. demonstrates superior performance over state-of-the-art approaches based rigorous testing mathematical analysis. Results indicate outperforms comparative regarding delay, average energy consumption, lifespan, throughput, up 38%, 30%, 150, 60%, respectively.

Language: Английский

Dynamic sink movement strategy for expedited query processing in Internet of things-based sensor networks DOI Creative Commons

Dongliang Xu

Journal of Engineering and Applied Science, Journal Year: 2025, Volume and Issue: 72(1)

Published: March 29, 2025

Abstract Wireless sensor networks (WSNs) represent an essential infrastructure that supports the Internet of things (IoT) and enables intelligent data collection from various contexts. In IoT-driven systems, nodes collect real-time data, initiate end-user or application requests, forward gathered to a cloud server. Query processing in WSN aims obtain accurate while conserving network resources. However, traditional static sink-based query methods often face challenges related lifetime lengthy delays. To mitigate these drawbacks, this paper proposes novel dynamic strategy (DSQPS) for IoT-enabled WSNs. DSQPS first calculates optimum number rendezvous points on by solving minimal set covering problem, followed Aquila Optimizer (AO), which optimizes mobile sinks. addition, optimized movement path sinks is determined, minimizing delays processing. demonstrates superior performance over state-of-the-art approaches based rigorous testing mathematical analysis. Results indicate outperforms comparative regarding delay, average energy consumption, lifespan, throughput, up 38%, 30%, 150, 60%, respectively.

Language: Английский

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