NDLI: Exploiting data fusion to improve the coverage of wireless sensor networks

Content Provider	ACM Digital Library
Author	Xing, Guoliang Jia, Xiaohua Tan, Rui Liu, Benyuan Wang, Jianping
Copyright Year	2012
Abstract	Wireless sensor networks (WSNs) have been increasingly available for critical applications such as security surveillance and environmental monitoring. An important performance measure of such applications is sensing coverage that characterizes how well a sensing field is monitored by a network. Although advanced collaborative signal processing algorithms have been adopted by many existing WSNs, most previous analytical studies on sensing coverage are conducted based on overly simplistic sensing models (e.g., the disc model) that do not capture the stochastic nature of sensing. In this paper, we attempt to bridge this gap by exploring the fundamental limits of coverage based on stochastic data fusion models that fuse noisy measurements of multiple sensors. We derive the scaling laws between coverage, network density, and signal-to-noise ratio (SNR). We show that data fusion can significantly improve sensing coverage by exploiting the collaboration among sensors when several physical properties of the target signal are known. In particular, for signal path loss exponent $of\textit{k}$ (typically between 2.0 and 5.0), ρf = $O(ρd^{1-1/k})where$ ρf and ρd are the densities of uniformly deployed sensors that achieve full coverage under the fusion and disc models, respectively. Moreover, data fusion can also reduce network density for regularly deployed networks and mobile networks where mobile sensors can relocate to fill coverage holes. Our results help understand the limitations of the previous analytical results based on the disc model and provide key insights into the design of WSNs that adopt data fusion algorithms. Our analyses are verified through extensive simulations based on both synthetic data sets and data traces collected in a real deployment for vehicle detection.
Starting Page	450
Ending Page	462
Page Count	13
File Format	PDF
ISSN	10636692
DOI	10.1109/TNET.2011.2164620
Volume Number	20
Issue Number	2
Journal	IEEE/ACM Transactions on Networking (TON)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-04-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Coverage Data fusion Mobility Performance limits Target detection Wireless sensor network (WSN)
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Networks and Communications Software Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Exploiting Data Fusion to Improve the Coverage of Wireless Sensor Networks

Data fusion improves the coverage of wireless sensor networks

Detection of intelligent mobile target in a mobile sensor network

Exploiting Reactive Mobility for Collaborative Target Detection in Wireless Sensor Networks

Spatial correlation and mobility-aware traffic modeling for wireless sensor networks

Lifetime maximization for connected target coverage in wireless sensor networks

The intrusion detection in mobile sensor network

Exploiting Mobility for Efficient Coverage in Sparse Wireless Sensor Networks

The Intrusion Detection in Mobile Sensor Network

Exploiting data fusion to improve the coverage of wireless sensor networks

Similar Documents

Exploiting Data Fusion to Improve the Coverage of Wireless Sensor Networks

Data fusion improves the coverage of wireless sensor networks

Detection of intelligent mobile target in a mobile sensor network

Exploiting Reactive Mobility for Collaborative Target Detection in Wireless Sensor Networks

Spatial correlation and mobility-aware traffic modeling for wireless sensor networks

Lifetime maximization for connected target coverage in wireless sensor networks

The intrusion detection in mobile sensor network

Exploiting Mobility for Efficient Coverage in Sparse Wireless Sensor Networks

The Intrusion Detection in Mobile Sensor Network

Exploiting data fusion to improve the coverage of wireless sensor networks