Paper Info
Title
LEAUCH: low-energy adaptive uneven clustering hierarchy for cognitive radio sensor network
Abstract
The integration of wireless sensor network (WSN) and cognitive radio (CR) technology enables a new paradigm of communication: cognitive radio sensor networks (CRSN). The existing WSN clustering algorithm cannot consider the advantage of channel resource brought by CR function in CRSN, and the CR network (CRN) clustering algorithm is designed based on the infinite energy nodes; thus both algorithms cannot operate with energy efficiency in CRSN. The paper proposes a low-energy adaptive uneven clustering hierarchy for CRSN, which can not only consider the advantage of the channel resource in reducing the energy consumption but also employ uneven clustering method for balancing the energy consumption among the cluster heads under multiple hops transmission means. Simulation results show that compared with the existing several typical clustering algorithms including WSN and CRSN clustering algorithms, low-energy adaptive clustering hierarchy (LEACH), HEED, energy-efficient unequal clustering (EEUC), cognitive LEACH (CogLEACH), and distributed spectrum-aware clustering (DSAC), the proposed algorithm can not only efficiently balance the energy consumption among cluster heads and network load in CRSN but also remarkably prolong the network lifetime.
Year
DOI
Venue
2015
10.1186/s13638-015-0354-x
EURASIP Journal on Wireless Communications and Networking
Keywords
Field
DocType
Cognitive radio sensor network, Channel resource, Uneven clustering, Energy consumption
Computer science,Efficient energy use,Computer network,Communication channel,Real-time computing,Cognitive radio sensor networks,Hierarchy,Cluster analysis,Wireless sensor network,Energy consumption,Cognitive radio
Journal
Volume
Issue
ISSN
2015
1
1687-1499
Citations 
PageRank 
References 
12
0.72
24
Authors
5
Name
Order
Citations
PageRank
Errong Pei1161.48
Haozhe Han2120.72
Zehua Sun3120.72
Bin Shen443134.86
Tianqi Zhang56821.52