Mobile device-target association optimization for connectivity enhancement in wireless IoT sensor networks

Wireless sensor networks are typically established in various areas of interest to observe phenomena, evaluate sensed data, and take appropriate action in response, which is embodied in 6G communications. To be able to do their jobs, which are getting increasingly complex, networks are combined with...

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Vydané v:Cluster computing Ročník 28; číslo 15; s. 978
Hlavní autori: Luong, Ho Viet Duc, Binh, Huynh Thi Thanh, Binh, Nguyen Thi My, Chien, Trinh Van
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.12.2025
Springer Nature B.V
Predmet:
Boolean
Branch and bound methods
Combinatorial analysis
Communication
Computer Communication Networks
Computer Science
Connectivity
Cooperation
Effectiveness
Electronic devices
Energy efficiency
Genetic algorithms
Heuristic methods
Internet of Things
Operating Systems
Optimization
Processor Architectures
Sensors
Unmanned aerial vehicles
Wireless sensor networks
Connectivity probability
Global optimum
Wireless IoT sensor networks
Low-complexity algorithm design
ISSN:1386-7857, 1573-7543
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Shrnutí:Wireless sensor networks are typically established in various areas of interest to observe phenomena, evaluate sensed data, and take appropriate action in response, which is embodied in 6G communications. To be able to do their jobs, which are getting increasingly complex, networks are combined with various emerging technologies such as the Internet of Things (IoT) and unmanned aerial vehicles (UAVs). These wireless IoT sensor networks frequently connect to many targets on the ground and process massive amounts of data over great distances. Each connectivity provides an association between mobile devices, and targets should be optimized due to the limited radio resources. This paper formulates a novel association problem to enhance sensing reliability. Mathematically, we minimize the number of mobile devices (MDs) activated to maintain the proper connectivity of individual targets. The constraint on a subset of activated MDs jointly serving a target makes a combinatorial problem whose global optimal solution can be obtained by the branch-and-bound method MTBB for small-scale networks. We propose effective designs based on the heuristic method and genetic algorithm that can find suboptimal solutions for large-scale networks with many MDs and targets. Numerical results demonstrate the effectiveness of the proposed algorithms in finding the global optimum and assigning MDs to maintain connection quality in the networks.
Bibliografia:ObjectType-Article-1
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ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-025-05647-9