Resource-efficient and secure distributed state estimation over wireless sensor networks: a survey
Xin-Chun Jia
International Journal of Systems Science, 2021, vol. 52, issue 16, 3368-3389
Abstract:
Wireless sensor networks (WSNs) are extensively adopted for remote monitoring and tracking scenarios, such as battlefield surveillance, target detection and tracking, traffic condition detection, power system monitoring and health monitoring, thanks to their promising benefits in terms of flexibility, reliability and cost-effectiveness. However, some critical WSN applications, such as intelligent transportation and smart grid monitoring, have stringent requirements in terms of resource budget and security. This paper provides a survey of the trending resource-efficient and secure techniques currently used with distributed estimation algorithms over WSNs. Recent progresses on these two major research trends are reviewed, respectively, for WSN-based monitoring systems. More specifically, the first part of the survey covers the state-of-the-art in resource-efficient distributed state estimation. The main results along this line of research are classified into protocol-based scheduling, static event-triggered scheduling, dynamic event-triggered scheduling and stochastic event-triggered scheduling. Then, in the second part, the latest results on secure distributed state estimation are reviewed, where secure distributed state estimation under data integrity attacks and data available attacks, and distributed attack detection are examined, respectively. Finally, several challenging issues in the context of distributed state estimation are discussed for potential future research.
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2021.1998843 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:52:y:2021:i:16:p:3368-3389
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20
DOI: 10.1080/00207721.2021.1998843
Access Statistics for this article
International Journal of Systems Science is currently edited by Visakan Kadirkamanathan
More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().