Destination-Based Cut Detection in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) often suffer from disrupted connectivity caused by its numerous aspects such as limited battery power of a node and unattended operation vulnerable to hostile tampering. The disruption of connectivity, often referred to as network cut, leads to ill-informed routing decisions, data loss, and waste of energy. A number of protocols have been proposed to efficiently detect network cuts, they focus solely on a cut that disconnects nodes from the base station. However, a cut detection scheme is truly useful when a cut is defined with respect to multiple destinations (i.e., target nodes), rather than a single base station. Thus, we extend the existing notion of cut detection, and propose an algorithm that enables sensor nodes to autonomously monitor the connectivity to multiple target nodes. We introduce a novel reactive cut detection solution, the Point-to-Point Cut Detection, where given any pair of source and destination, a source is able to locally determine whether the destination is reachable or not. Furthermore, we propose a lightweight proactive cut detection algorithm specifically designed for a small set of target destinations. We prove the effectiveness of the proposed algorithms through extensive simulations.

[1]  Deborah Estrin,et al.  ASCENT: adaptive self-configuring sensor networks topologies , 2004, IEEE Transactions on Mobile Computing.

[2]  Gang Zhou,et al.  VigilNet: An integrated sensor network system for energy-efficient surveillance , 2006, TOSN.

[3]  Wei Zhou,et al.  DistressNet: a wireless ad hoc and sensor network architecture for situation management in disaster response , 2010, IEEE Communications Magazine.

[4]  Cem Ersoy,et al.  Multiple sink network design problem in large scale wireless sensor networks , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[5]  Abhimanyu Das,et al.  Data acquisition in multiple-sink sensor networks , 2005, MOCO.

[6]  Jon M. Kleinberg,et al.  Detecting a Network Failure , 2004, Internet Math..

[7]  Myounggyu Won,et al.  Towards robustness and energy efficiency of cut detection in wireless sensor networks , 2011, Ad Hoc Networks.

[8]  Sang Hyuk Son,et al.  On composability of localization protocols for wireless sensor networks , 2008, IEEE Network.

[9]  John A. Stankovic,et al.  Context-aware wireless sensor networks for assisted living and residential monitoring , 2008, IEEE Network.

[10]  Anne-Marie Kermarrec,et al.  Visibility-Graph-Based Shortest-Path Geographic Routing in Sensor Networks , 2009, IEEE INFOCOM 2009.

[11]  Csaba D. Tóth,et al.  Detecting cuts in sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[12]  Rolf Winter,et al.  A partition detection system for mobile ad-hoc networks , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[13]  Tamás Kalmár-Nagy,et al.  Distributed cut detection in sensor networks , 2008, SenSys '08.

[14]  Chee-Yee Chong,et al.  Sensor networks: evolution, opportunities, and challenges , 2003, Proc. IEEE.

[15]  Aleksandrs Slivkins,et al.  Network failure detection and graph connectivity , 2004, SODA '04.

[16]  M. S. Corson,et al.  A highly adaptive distributed routing algorithm for mobile wireless networks , 1997, Proceedings of INFOCOM '97.

[17]  Brad Karp,et al.  GPSR: greedy perimeter stateless routing for wireless networks , 2000, MobiCom '00.