Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/2437
Title: Performance evaluation of cluster-based target tracking protocols for wireless sensor networks
Authors: Alaybeyoğlu, Ayşegül
Dağdeviren, Orhan
Erciyeş, Kayhan
Kantarcı, Aylin
Dağdeviren, Orhan
Izmir Institute of Technology. Computer Engineering
Keywords: Target tracking
Clustering algorithms
Wireless sensor networks
Gauss-Markov models
Network protocols
Issue Date: 2009
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Alaybeyoğlu, A., Dağdeviren, O., Erciyeş, K., and Kantarcı, A. (2009, September 14-16). Performance evaluation of cluster-based target tracking protocols for wireless sensor networks. Paper presented at the 24th International Symposium on Computer and Information Sciences, ISCIS 2009. doi:10.1109/ISCIS.2009.5291806
Abstract: Target tracking is an important application type for wireless sensor networks (WSN). Recently, various approaches [1-11] are proposed to maintain the accurate tracking of the targets as well as low energy consumption. Clustering is a fundamental technique to manage the scarce network resources [12-19]. The message complexity of an application can be significantly decreased when it is redesigned on top of a clustered network. Clustering has provided an efficient infrastructure in many existing studies [1-8]. The clusters can be constructed before the target enters the region which is called the static method [1-4] or clusters are created by using received signal strength (RSS) from target which is called the dynamic method [5-8]. In this paper we provide simulations of static and dynamic clustering algorithms against various mobility models and target speeds. The mobility models that we applied are Random Waypoint Model, Random Direct Model and Gauss Markov Model. We provide metrics to measure the tracking performance of both approaches. We show that the dynamic clustering is favorable in terms of tracking accuracy whereas the energy consumption of static clustering is significantly smaller. We also show that the target moving with Gauss Markov Model can be tracked more accurately than the other models.
Description: 24th International Symposium on Computer and Information Sciences, ISCIS 2009; Guzelyurt; Cyprus; 14 September 2009 through 16 September 2009
URI: http://doi.org/10.1109/ISCIS.2009.5291806
http://hdl.handle.net/11147/2437
ISBN: 9781424450237
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File Description SizeFormat 
2437.pdfConference Paper728.94 kBAdobe PDFThumbnail
View/Open
Show full item record

CORE Recommender

SCOPUSTM   
Citations

14
checked on Jul 31, 2021

Page view(s)

12
checked on Aug 4, 2021

Download(s)

16
checked on Aug 4, 2021

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.