Multiple Mobile Target Tracking in Wireless Sensor Networks
An object tracking sensor network (OTSN) is made of $$m$$ static wireless sensors scattered throughout a geographical area for tracking $$n$$ mobiletargets. Assuming that sensors have non-rechargeable batteries, one of the most critical aspects of OTSN is energy consumption. In this paper, we propos...
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| Published in | Swarm Intelligence Based Optimization pp. 123 - 130 |
|---|---|
| Main Authors | , , |
| Format | Book Chapter |
| Language | English |
| Published |
Cham
Springer International Publishing
01.01.2014
Springer |
| Series | Lecture Notes in Computer Science |
| Subjects | |
| Online Access | Get full text |
| ISBN | 3319129694 9783319129693 |
| ISSN | 0302-9743 1611-3349 |
| DOI | 10.1007/978-3-319-12970-9_14 |
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| Abstract | An object tracking sensor network (OTSN) is made of $$m$$ static wireless sensors scattered throughout a geographical area for tracking $$n$$ mobiletargets. Assuming that sensors have non-rechargeable batteries, one of the most critical aspects of OTSN is energy consumption. In this paper, we propose linear programming models which handle two missions : monitoring and reporting data to a base station, and two distinct problems : minimize energy consumption and maximize network lifetime. We suppose that trajectories of targets are known and targets should be monitored by sensors. To reach our goals, we schedule the active and sleep states of the sensors and route the data to a base station while keeping track of the targets. To solve our problems, we process a temporal discretization according to the intersection points between the trajectories and the sensing ranges of the sensors. The obtained sets of sensors for each time window help us to create linear programming models. These basic problems offer perspectives in performance evaluation of energy-conservation protocols and distributed algorithms in wireless sensor networks. |
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| AbstractList | An object tracking sensor network (OTSN) is made of m static wireless sensors scattered throughout a geographical area for tracking n mobile targets. Assuming that sensors have non-rechargeable batteries, one of the most critical aspects of OTSN is energy consumption. In this paper, we propose linear programming models which handle two missions: monitoring and reporting data to a base station, and two distinct problems : minimize energy consumption and maximize network lifetime. We suppose that trajectories of targets are known and targets should be monitored by sensors. To reach our goals, we schedule the active and sleep states of the sensors and route the data to a base station while keeping track of the targets. To solve our problems, we process a temporal discretization according to the intersection points between the trajectories and the sensing ranges of the sensors. The obtained sets of sensors for each time window help us to create linear programming models. These basic problems offer perspectives in performance evaluation of energy-conservation protocols and distributed algorithms in wireless sensor networks. An object tracking sensor network (OTSN) is made of $$m$$ static wireless sensors scattered throughout a geographical area for tracking $$n$$ mobiletargets. Assuming that sensors have non-rechargeable batteries, one of the most critical aspects of OTSN is energy consumption. In this paper, we propose linear programming models which handle two missions : monitoring and reporting data to a base station, and two distinct problems : minimize energy consumption and maximize network lifetime. We suppose that trajectories of targets are known and targets should be monitored by sensors. To reach our goals, we schedule the active and sleep states of the sensors and route the data to a base station while keeping track of the targets. To solve our problems, we process a temporal discretization according to the intersection points between the trajectories and the sensing ranges of the sensors. The obtained sets of sensors for each time window help us to create linear programming models. These basic problems offer perspectives in performance evaluation of energy-conservation protocols and distributed algorithms in wireless sensor networks. |
| Author | Sevaux, Marc Rossi, André Lersteau, Charly |
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| Editor | Idoumghar, Lhassane Lepagnot, Julien Siarry, Patrick |
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| Notes | Original Abstract: An object tracking sensor network (OTSN) is made of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$m$$\end{document}static wireless sensors scattered throughout a geographical area for tracking \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$n$$\end{document}mobiletargets. Assuming that sensors have non-rechargeable batteries, one of the most critical aspects of OTSN is energy consumption. In this paper, we propose linear programming models which handle two missions : monitoring and reporting data to a base station, and two distinct problems : minimize energy consumption and maximize network lifetime. We suppose that trajectories of targets are known and targets should be monitored by sensors. To reach our goals, we schedule the active and sleep states of the sensors and route the data to a base station while keeping track of the targets. To solve our problems, we process a temporal discretization according to the intersection points between the trajectories and the sensing ranges of the sensors. The obtained sets of sensors for each time window help us to create linear programming models. These basic problems offer perspectives in performance evaluation of energy-conservation protocols and distributed algorithms in wireless sensor networks. |
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| PublicationSubtitle | First International Conference, ICSIBO 2014, Mulhouse, France, May 13-14, 2014. Revised Selected Papers |
| PublicationTitle | Swarm Intelligence Based Optimization |
| PublicationYear | 2014 |
| Publisher | Springer International Publishing Springer |
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| RelatedPersons | Kleinberg, Jon M. Mattern, Friedemann Naor, Moni Mitchell, John C. Terzopoulos, Demetri Steffen, Bernhard Pandu Rangan, C. Kanade, Takeo Kittler, Josef Weikum, Gerhard Hutchison, David Tygar, Doug |
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| Snippet | An object tracking sensor network (OTSN) is made of $$m$$ static wireless sensors scattered throughout a geographical area for tracking $$n$$ mobiletargets.... An object tracking sensor network (OTSN) is made of m static wireless sensors scattered throughout a geographical area for tracking n mobile targets. Assuming... |
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| StartPage | 123 |
| SubjectTerms | Computer Science Energy consumption minimization Lifetime maximization Multiple target tracking Operations Research Wireless sensor networks |
| Title | Multiple Mobile Target Tracking in Wireless Sensor Networks |
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