Fuzzy ring-overlapping range-free (FRORF) localization method for wireless sensor networks

被引:17
作者
Velimirovic, Andrija S. [1 ]
Djordjevic, Goran Lj. [1 ]
Velimirovic, Maja M. [1 ]
Jovanovic, Milica D. [1 ]
机构
[1] Univ Nis, Fac Elect Engn, Nish 18000, Serbia
关键词
Wireless sensor networks; Localization; RSS; Ring-overlapping localization; Fuzzy set theory;
D O I
10.1016/j.comcom.2012.05.006
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The sensor node localization with an acceptable accuracy is a fundamental and important problem for location-aware applications of wireless sensor networks (WSNs). Among numerous localization schemes proposed specifically for WSNs, the received signal strength (RSS) based range-free localization techniques have attracted considerable research interest for their simplicity and low cost. However, these techniques suffer from significant estimation errors due to low accuracy of RSS measurements influenced by irregular radio propagation. In order to cope with the problem of RSS uncertainty, in this paper we propose a fuzzy set-based localization method, called fuzzy ring overlapping range free (FROFR) localization. Similar to other area-based localization schemes, FRORF relies on beacon signals broadcasted by anchors to isolate a region of the localization space where the sensor node most probably resides. As an extension to the concept of ring-overlapping localization, FRORF first represents overlapping rings as fuzzy sets with ambiguous boundaries in contrast to fixed intervals of RSS values, and then generates fuzzy set of regions by intersecting rings from different fuzzy ring sets. The degrees of sensor node membership to regions in the fuzzy set of regions are used to determine the location estimate. The results obtained from simulations demonstrate that our solution improve localization accuracy in the presence of radio irregularity, and even for the case without radio irregularity. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:1590 / 1600
页数:11
相关论文
共 24 条
[1]   Environmental-Adaptive RSSI-Based Indoor Localization [J].
Ahn, Hyo-Sung ;
Yu, Wonpil .
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2009, 6 (04) :626-633
[2]   Wireless sensor networks: a survey [J].
Akyildiz, IF ;
Su, W ;
Sankarasubramaniam, Y ;
Cayirci, E .
COMPUTER NETWORKS, 2002, 38 (04) :393-422
[3]  
[Anonymous], 2007, INT J SENS NETW
[4]   GPS-less low-cost outdoor localization for very small devices [J].
Bulusu, N ;
Heidemann, J ;
Estrin, D .
IEEE PERSONAL COMMUNICATIONS, 2000, 7 (05) :28-34
[5]   Time-of-arrival based localization under NLOS conditions [J].
Chan, YT ;
Tsui, WY ;
So, HC ;
Ching, PC .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2006, 55 (01) :17-24
[6]   Mobile Element Assisted Cooperative Localization for Wireless Sensor Networks with Obstacles [J].
Chen, Hongyang ;
Shi, Qingjiang ;
Tan, Rui ;
Poor, H. Vincent ;
Sezaki, Kaoru .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2010, 9 (03) :956-963
[7]  
Dubois D.J., 1980, Fuzzy sets and systems: theory and applications
[8]  
He T., 2003, Annual International Conference on Mobile Computing and Networking, P81
[9]  
Karl H, 2005, PROTOCOLS AND ARCHITECTURES FOR WIRELESS SENSOR NETWORKS, P1, DOI 10.1002/0470095121
[10]   Resilient localization for sensor networks in outdoor environments [J].
Kwon, YM ;
Mechitov, K ;
Sundresh, S ;
Kim, W ;
Agha, G .
25TH IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS, PROCEEDINGS, 2005, :643-652