Decentralized boundary detection without location information in wireless sensor networks

In wireless sensor networks (WSNs) deployed in an outdoor environment, obstacles may occur as a result of a non-uniform distribution of the sensor nodes or the presence of barriers. These obstacles result in a degradation of the network performance, so obstacle identification is a major concern in most WSN applications. This paper develops a Decentralized Boundary Detection (DBD) algorithm for identifying sensor nodes near a hole or obstacle in the WSN. The algorithm does not require any knowledge of the node locations or distances between two nodes. The detection capability is provided even in networks where the sensor nodes have a non-unit disk communication range.

[1]  Yunhao Liu,et al.  Fine-grained boundary recognition in wireless ad hoc and sensor networks by topological methods , 2009, MobiHoc '09.

[2]  Jindong Tan,et al.  Mobile sensor deployment for a dynamic cluster-based target tracking sensor network , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Sándor P. Fekete,et al.  Deterministic boundary recognition and topology extraction for large sensor networks , 2005, SODA '06.

[4]  Mi Lu,et al.  A distributed algorithm for the dead end problem of location based routing in sensor networks , 2005, IEEE Transactions on Vehicular Technology.

[5]  Leonidas J. Guibas,et al.  Locating and bypassing routing holes in sensor networks , 2004, IEEE INFOCOM 2004.

[6]  Jie Gao,et al.  Boundary recognition in sensor networks by topological methods , 2006, MobiCom '06.

[7]  Stefan Funke,et al.  Topological hole detection in wireless sensor networks and its applications , 2005, DIALM-POMC '05.

[8]  Stefan Funke,et al.  Hole detection or: "how much geometry hides in connectivity?" , 2006, SCG '06.

[9]  Kai-Ten Feng,et al.  Greedy Anti-Void Routing Protocol for Wireless Sensor Networks , 2007, IEEE Communications Letters.

[10]  Yingping Huang.  Obstacle detection in urban traffic using stereovision , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[11]  Sesh Commuri,et al.  Energy-efficient approaches to coverage holes detection in wireless sensor networks , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

[12]  Michael Kaufmann,et al.  A New Approach for Boundary Recognition in Geometric Sensor Networks , 2005, CCCG.

[13]  P. Lombardi,et al.  Unified stereovision for ground, road, and obstacle detection , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[14]  Pedro José Marrón,et al.  On Boundary Recognition without Location Information in Wireless Sensor Networks , 2008, 2008 International Conference on Information Processing in Sensor Networks (ipsn 2008).

[15]  Lali Barrière,et al.  Robust position-based routing in wireless Ad Hoc networks with unstable transmission ranges , 2001, DIALM '01.

[16]  Jeffrey Byrne,et al.  Stereo based obstacle detection for an unmanned air vehicle , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[17]  Alberto Broggi,et al.  Obstacle Detection with Stereo Vision for Off-Road Vehicle Navigation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[18]  Abubakr Muhammad,et al.  Coverage and hole-detection in sensor networks via homology , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[19]  Dirk Timmermann,et al.  Distributed obstacle localization in large wireless sensor networks , 2006, IWCMC '06.

[20]  Guangbin Fan,et al.  Avoid 'void' in geographic routing for data aggregation in sensor networks , 2006, Int. J. Ad Hoc Ubiquitous Comput..

[21]  David K. Hunter,et al.  Distributed Coordinate-free Hole Detection and Recovery , 2006 .