DocumentCode
483664
Title
Efficient data reporting for object tracking in wireless sensor networks with mobile sinks
Author
Hwang, Shiow-Fen ; Lu, Kun-Hsien ; Yang, Liang-Ren ; Dow, Chyi-Ren
Author_Institution
Dept. of Inf. Eng. & Comput. Sci., Feng Chia Univ., Taichung
fYear
2008
fDate
14-16 Oct. 2008
Firstpage
1
Lastpage
5
Abstract
Object tracking is an important application in wireless sensor networks (WSNs). However, most of researches focus on how to track mobile objects accurately and do not consider data reporting, especially when sinks move arbitrarily in the sensor field. In this paper, we propose an efficient data reporting method for object tracking in WSNs with mobile sinks. In our network environment, the sensor field is divided into several grids. Only some nodes are elected as active nodes for tracking the object and reporting data, the others are in sleep mode for saving energy. Moreover, a simple scheduling is given to balance the energy consumption of nodes. To guide the current position of the sink and reduce the update cost as the sink moves, we design an elegant weight function for active nodes. By the weight function, the tracking data can be forwarded to the mobile sink efficiently. In addition, we also propose a simple object tracking method in which an object can be detected by two or more active nodes with tracking flags. Simulation results show that our proposed method outperforms than TNT and SNEM in terms of the energy consumption and average hop counts.
Keywords
object detection; scheduling; tracking; wireless sensor networks; data reporting method; elegant weight function; mobile object tracking; mobile sink; node energy consumption; object detection; scheduling scheme; wireless sensor network; Animals; Broadcasting; Counting circuits; Energy consumption; Monitoring; Object detection; Protocols; Scheduling; Wireless communication; Wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, 2008. APCC 2008. 14th Asia-Pacific Conference on
Conference_Location
Tokyo
Print_ISBN
978-4-88552-232-1
Electronic_ISBN
978-4-88552-231-4
Type
conf
Filename
4773829
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