GTIACO: energy efficient clustering algorithm based on game theory and improved ant colony optimization

Recently, wireless sensor networks have been widely used for environmental and structural safety monitoring. However, node batteries cannot be replaced or easily recharged in harsh environments. Maximizing network lifetime remains a challenging issue in designing WSN routing. This paper introduces G...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Telecommunication systems Jg. 86; H. 3; S. 463 - 480
Hauptverfasser: Wan, Hang, Qiu, Zhizhuo, Quan, Rui, David, Michael, Derigent, William
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.07.2024
Springer Nature B.V
Springer Verlag (Germany)
Schlagworte:
Algorithms
Ant colony optimization
Artificial Intelligence
Business and Management
Clustering
Clusters
Computer Communication Networks
Computer Science
Game theory
Heuristic methods
IT in Business
Networking and Internet Architecture
Probability Theory and Stochastic Processes
Stability
Structural safety
Telecommunications systems
Transmission efficiency
Wireless sensor networks
Ant colony optimization
WSN
Routing protocol
Game theory
Energy management
Network lifecycle
Game Theory
Ant Colony Optimization
Network Lifecycle
Energy Management
Routing Protocol
ISSN:1018-4864, 1572-9451
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Recently, wireless sensor networks have been widely used for environmental and structural safety monitoring. However, node batteries cannot be replaced or easily recharged in harsh environments. Maximizing network lifetime remains a challenging issue in designing WSN routing. This paper introduces GTIACO, a novel metaheuristic clustering protocol. It employs an optimal cluster head function to determine cluster number and utilizes game theory for selecting optimal cluster heads. To optimize inter-cluster routing, improved ant colony optimization (ACO) is introduced to construct gathering paths from clusters to the base station. Both blind pathways, pheromone concentration, and angle factors are considered to improve path exploration and transmission efficiency in ant colonies. To assess network performance, various scenarios involving different base station placements and network densities are examined. Experimental results demonstrate GTIACO's superiority over LEACH, ACO, SEP, and PRESPE protocols in network lifetime, stability, energy, and throughput. The proposed GTIACO shows an improvement of at least 4.3% in network lifetime and 32.8% in network throughout. It exhibits superior stability and transmission efficiency across diverse network densities.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1018-4864
1572-9451
DOI:10.1007/s11235-024-01132-7