Robust scheduling of wireless sensor networks for target tracking under uncertainty

•This paper addresses a target tracking robustness problem in Wireless Sensor Networks.•A maximum stability radius schedule is computed with a pseudo-polynomial algorithm.•Two classes of upper bounds are exploited to speed up convergence.•Large problem instances with up to 1000 sensors can be solved...

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Veröffentlicht in:European journal of operational research Jg. 252; H. 2; S. 407 - 417
Hauptverfasser: Lersteau, Charly, Rossi, André, Sevaux, Marc
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 16.07.2016
Elsevier Sequoia S.A
Elsevier
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ISSN:0377-2217, 1872-6860
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Abstract •This paper addresses a target tracking robustness problem in Wireless Sensor Networks.•A maximum stability radius schedule is computed with a pseudo-polynomial algorithm.•Two classes of upper bounds are exploited to speed up convergence.•Large problem instances with up to 1000 sensors can be solved in less than 20 seconds. An object tracking sensor network (OTSN) is a wireless sensor network designed to track moving objects in its sensing area. It is made of static sensors deployed in a region for tracking moving targets. Usually, these sensors are equipped of a sensing unit and a non-rechargeable battery. The investigated mission involves a moving target with a known trajectory, such as a train on a railway or a plane in an airline route. In order to save energy, the target must be monitored by exactly one sensor at any time. In our context, the sensors may be not accessible during the mission and the target can be subject to earliness or tardiness. Therefore, our aim is to build a static schedule of sensing activities that resists to these perturbations. A pseudo-polynomial two-step algorithm is proposed. First, a discretization step processes the input data, and a mathematical formulation of the scheduling problem is proposed. Then, a dichotomy approach that solves a transportation problem at every iteration is introduced; the very last step is addressed by solving a linear program.
AbstractList An object tracking sensor network (OTSN) is a wireless sensor network designed to track moving objects in its sensing area. It is made of static sensors deployed in a region for tracking moving targets. Usually, these sensors are equipped of a sensing unit and a non-rechargeable battery. The investigated mission involves a moving target with a known trajectory, such as a train on a railway or a plane in an airline route. In order to save energy, the target must be monitored by exactly one sensor at any time. In our context, the sensors may be not accessible during the mission and the target can be subject to earliness or tardiness. Therefore, our aim is to build a static schedule of sensing activities that resists to these perturbations. A pseudo-polynomial two-step algorithm is proposed. First, a discretization step processes the input data, and a mathematical formulation of the scheduling problem is proposed. Then, a dichotomy approach that solves a transportation problem at every iteration is introduced; the very last step is addressed by solving a linear program.
•This paper addresses a target tracking robustness problem in Wireless Sensor Networks.•A maximum stability radius schedule is computed with a pseudo-polynomial algorithm.•Two classes of upper bounds are exploited to speed up convergence.•Large problem instances with up to 1000 sensors can be solved in less than 20 seconds. An object tracking sensor network (OTSN) is a wireless sensor network designed to track moving objects in its sensing area. It is made of static sensors deployed in a region for tracking moving targets. Usually, these sensors are equipped of a sensing unit and a non-rechargeable battery. The investigated mission involves a moving target with a known trajectory, such as a train on a railway or a plane in an airline route. In order to save energy, the target must be monitored by exactly one sensor at any time. In our context, the sensors may be not accessible during the mission and the target can be subject to earliness or tardiness. Therefore, our aim is to build a static schedule of sensing activities that resists to these perturbations. A pseudo-polynomial two-step algorithm is proposed. First, a discretization step processes the input data, and a mathematical formulation of the scheduling problem is proposed. Then, a dichotomy approach that solves a transportation problem at every iteration is introduced; the very last step is addressed by solving a linear program.
Author Sevaux, Marc
Rossi, André
Lersteau, Charly
Author_xml – sequence: 1
  givenname: Charly
  surname: Lersteau
  fullname: Lersteau, Charly
  email: charly.lersteau@univ-ubs.fr
  organization: Université de Bretagne-Sud – Lab-STICC, CNRS, UMR 6285 Lorient, France
– sequence: 2
  givenname: André
  surname: Rossi
  fullname: Rossi, André
  email: andre.rossi@univ-angers.fr
  organization: Université d’Angers – LERIA, Angers, France
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  givenname: Marc
  orcidid: 0000-0003-3855-9072
  surname: Sevaux
  fullname: Sevaux, Marc
  email: marc.sevaux@univ-ubs.fr
  organization: Université de Bretagne-Sud – Lab-STICC, CNRS, UMR 6285 Lorient, France
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Issue 2
Keywords Wireless sensor networks
Target tracking
Uncertainty
Robustness
Stability radius
robustness
wireless sensor networks
stability radius
uncertainty
target tracking
Language English
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Snippet •This paper addresses a target tracking robustness problem in Wireless Sensor Networks.•A maximum stability radius schedule is computed with a...
An object tracking sensor network (OTSN) is a wireless sensor network designed to track moving objects in its sensing area. It is made of static sensors...
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SubjectTerms Computer Science
Construction
Detection
Energy efficiency
Linear programming
Moving targets
Operations Research
Remote sensors
Robustness
Scheduling
Scheduling algorithms
Sensors
Stability radius
Studies
Target tracking
Tracking
Tracking control systems
Uncertainty
Wireless networks
Wireless sensor networks
Title Robust scheduling of wireless sensor networks for target tracking under uncertainty
URI https://dx.doi.org/10.1016/j.ejor.2016.01.018
https://www.proquest.com/docview/1774194733
https://www.proquest.com/docview/1816047955
https://hal.science/hal-01254974
Volume 252
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