Paper Info
Title
Intelligent data fusion algorithm based on hybrid delay-aware adaptive clustering in wireless sensor networks
Abstract
Data fusion can effectively reduce the amount of data transmission and network energy consumption in wireless sensor networks (WSNs). However the existing data fusion schemes lead to additional delay overhead and power consumptions. In order to improve the performance of WSNs, an intelligent data fusion algorithm based on hybrid delay-aware clustering (HDC) in WSNs is proposed, which combines the advantages of single-layer cluster structure and multi-layer cluster structure, and adaptive selects the clustering patterns of the cluster by the decision function to achieve the tradeoff between network delay and energy consumption. The network model of HDC is presented, and theoretical analysis of the delay and energy consumption of single-layer cluster and multi-layer cluster are provided. And the energy efficient clustering algorithm and the dynamic cluster head re-selection algorithm are proposed to optimize network energy consumption and load balancing of the network. Simulation results show that, compared with the existing delay-aware models, the proposed scheme can effectively reduce the network delay, network energy consumption, and extend the network lifetime simultaneously.
Year
DOI
Venue
2020
10.1016/j.future.2019.10.001
Future Generation Computer Systems
Keywords
Field
DocType
Intelligent data fusion,Delay-aware,Energy consumption,Adaptive clustering,Wireless sensor networks
Network delay,Data transmission,Load balancing (computing),Computer science,Sensor fusion,Real-time computing,Cluster analysis,Energy consumption,Wireless sensor network,Network model,Distributed computing
Journal
Volume
ISSN
Citations 
104
0167-739X
1
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Xiaozhu Liu120.69
Rongbo Zhu232136.11
Ashiq Anjum333338.33
Jun Wang49228736.82
Hao Zhang5913.51
Maode Ma61255163.24