Title
Localization with Graph Diffusion Property.
Abstract
Node localization is an essential issue in wireless sensor networks (WSNs). Many range-free localization methods have been proposed to satisfy the requirement of low-system cost. However, some range-free methods only depend on network connectivity, and others only utilize the proximity information attached in neighborhood ordering. To employ the strength of the above two aspects, this paper introduces a new metric system called Combined and Weighted Diffusion Distance (CWDD). CWDD is designed to obtain the relative distance among nodes based on both graph diffusion property and neighbor information. We implement our design by embedding CWDD into two well-known localization algorithms and evaluate it by extensive simulations. Results show that our design improves the localization performance in large scale and non-uniform sensor networks, which reduces positioning errors by as much as 26%.
Year
DOI
Venue
2017
10.3390/s17071636
SENSORS
Keywords
Field
DocType
node localization,graph diffusion property,wireless sensor networks
Metric system,Network connectivity,Graph,Mathematical optimization,Embedding,Electronic engineering,Engineering,Wireless sensor network,Computer engineering
Journal
Volume
Issue
Citations 
17
7.0
0
PageRank 
References 
Authors
0.34
14
5
Name
Order
Citations
PageRank
Pengpeng Chen112317.75
Yuqing Yin212.41
Shouwan Gao382.24
Qiang Niu487.67
jun gu533.25