Reactive localisation in underwater wireless sensor networks with self-healing

Authors:
Mohamed K. Watfa;Tala Nsouli;Maya El Ayach;Omar El Ayach
Affiliations:
Faculty of Computer Science and Engineering, University of Wollongong in Dubai, Dubai, UAE;Computer Science/Computer Engineering Department, American University of Beirut, Beirut, Lebanon;Computer Science/Computer Engineering Department, American University of Beirut, Beirut, Lebanon;Computer Science/Computer Engineering Department, American University of Beirut, Beirut, Lebanon
Venue:
International Journal of Intelligent Systems Technologies and Applications
Year:
2013

Citing 4
Cited 0

Robust distributed network localization with noisy range measurements

SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Node Discovery Protocol and Localization for Distributed Underwater Acoustic Networks

AICT-ICIW '06 Proceedings of the Advanced Int'l Conference on Telecommunications and Int'l Conference on Internet and Web Applications and Services
Localization in underwater sensor networks: survey and challenges

WUWNet '06 Proceedings of the 1st ACM international workshop on Underwater networks
AUV-Aided Localization for Underwater Sensor Networks

WASA '07 Proceedings of the International Conference on Wireless Algorithms,Systems and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present a novel technique for localising an event of interest in an underwater environment monitored by an underwater sensor network. Instead of proactively localising every single node in the network as all proposed techniques set out to do, we approach localisation from a reactive angle. We reduce the localisation problem to the problem of finding 4-Node Coverage. Whenever a node detects an event, it is reactively localised using the anchor nodes, and the sink is supplied with the necessary information. By limiting the sensing range of the sensor nodes, once we have obtained the location of the node that has detected the event, we have a rough estimation of the location of the event. We show that in terms of energy consumption, this localisation technique far surpasses others.