Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/9745
Title: | Fttrack: Fault-tolerant target tracking in binary sensor networks | Authors: | Laoudias, Christos Michaelides, Michalis P. Panayiotou, Christos G. |
metadata.dc.contributor.other: | Μιχαηλίδης, Μιχάλης | Major Field of Science: | Natural Sciences | Field Category: | Computer and Information Sciences;Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Binary data;Fault tolerance;Localization;Sensor-state estimation;Target tracking;Wireless sensor networks | Issue Date: | 1-Jun-2014 | Source: | ACM Transactions on Sensor Networks, 2014, vol. 10, no. 4, pp. 64 | Volume: | 10 | Issue: | 4 | End page: | 64 | Journal: | ACM Transactions on Sensor Networks | Abstract: | The provision of accurate and reliable localization and tracking information for a target moving inside a binaryWireless Sensor Network (WSN) is quite challenging, especially when sensor failures due to hardware and/or software malfunctions or adversary attacks are considered. Most tracking algorithms assume faultfree scenarios and exploit all binary sensor observations, thus their accuracy may degrade when faults are present in the field. Spatiotemporal information available while the target is traversing the sensor field can be used not only for tracking the target, but also for detecting certain types of faults that appear highly correlated both in time and space. Our main contribution is ftTRACK, a target tracking architecture that is resilient to sensor faults and consists of three main components, namely the sensor health-state estimator, a fault-tolerant localization algorithm, and a location smoothing component. The key idea in the ftTRACK architecture lies in the sensor health-state estimator that leverages spatiotemporal information from previous estimation steps to intelligently choosewhich sensors to employ in the localization and tracking tasks. Simulation results indicate that ftTRACK maintains a high level of tracking accuracy, even when a large number of sensors fail. | URI: | https://hdl.handle.net/20.500.14279/9745 | ISSN: | 15504859 | DOI: | 10.1145/2538509 | Rights: | © ACM | Type: | Article | Affiliation : | Cyprus University of Technology University of Cyprus |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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