Distributed resource management and matching in sensor networks

We consider a scenario in which there are resources at or near nodes of a network, which are either static (e.g. fire stations, parking spots) or mobile (e.g. police cars). Over time, events (fires, crime reports, cars looking for parking) arise one-by-one at arbitrary nodes, and need to be quickly...

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Veröffentlicht in:2009 International Conference on Information Processing in Sensor Networks S. 97 - 108
Hauptverfasser: Gao, Jie, Guibas, Leonidas, Milosavljevic, Nikola, Dengpan Zhou
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Washington, DC, USA IEEE Computer Society 13.04.2009
IEEE
Schriftenreihe:ACM Conferences
Schlagworte:
Computer networks
Computer science
Computer systems organization > Architectures > Distributed architectures
Computing methodologies > Modeling and simulation > Simulation evaluation
Costs
Distributed computing
Distributed Matching
Event detection
Fires
Intelligent sensors
Mathematics of computing > Mathematical analysis > Mathematical optimization
Networks > Network services > Network management
Optimal matching
Resource management
Sensor Networks
Software and its engineering > Software organization and properties > Software system structures > Distributed systems organizing principles
Theory of computation > Design and analysis of algorithms > Data structures design and analysis > Pattern matching
Theory of computation > Design and analysis of algorithms > Mathematical optimization
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ISBN:1424451086, 9781424451081
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Abstract We consider a scenario in which there are resources at or near nodes of a network, which are either static (e.g. fire stations, parking spots) or mobile (e.g. police cars). Over time, events (fires, crime reports, cars looking for parking) arise one-by-one at arbitrary nodes, and need to be quickly matched to and serviced by an appropriate nearby resource, without knowledge of future requests, and without the ability to alter any decision once it has been made. We develop distributed algorithms to direct available resources in the network to these events (or vice versa) in a coordinated fashion, so that no two resources are assigned to the same event, and the total distance of the events from their matched resources is minimized. The key idea is to extract, in a preprocessing stage, a well-separated tree metric that approximates the original network metric by a logarithmic distortion, allowing greedy matching algorithms to generate close to optimal matchings, and enabling communication-efficient probing-based algorithms for events to detect nearby available resources. The distributed matching algorithm requires no global coordination and achieves polylogarithmic performance ratio in both online and offline settings. Simulation experiments corroborate the theoretical results on solution quality and further evaluate the communication costs of our scheme in practice.
AbstractList We consider a scenario in which there are resources at or near nodes of a network, which are either static (e.g. fire stations, parking spots) or mobile (e.g. police cars). Over time, events (fires, crime reports, cars looking for parking) arise one-by-one at arbitrary nodes, and need to be quickly matched to and serviced by an appropriate nearby resource, without knowledge of future requests, and without the ability to alter any decision once it has been made. We develop distributed algorithms to direct available resources in the network to these events (or vice versa) in a coordinated fashion, so that no two resources are assigned to the same event, and the total distance of the events from their matched resources is minimized. The key idea is to extract, in a preprocessing stage, a well-separated tree metric that approximates the original network metric by a logarithmic distortion, allowing greedy matching algorithms to generate close to optimal matchings, and enabling communication-efficient probing-based algorithms for events to detect nearby available resources. The distributed matching algorithm requires no global coordination and achieves polylogarithmic performance ratio in both online and offline settings. Simulation experiments corroborate the theoretical results on solution quality and further evaluate the communication costs of our scheme in practice.
Author Gao, Jie
Milosavljevic, Nikola
Dengpan Zhou
Guibas, Leonidas
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  givenname: Jie
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  fullname: Guibas, Leonidas
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  surname: Milosavljevic
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  organization: Department of Computer Science, Stanford University, CA 94305, USA
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  surname: Dengpan Zhou
  fullname: Dengpan Zhou
  organization: Department of Computer Science, Stony Brook University, NY 11794, USA
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Snippet We consider a scenario in which there are resources at or near nodes of a network, which are either static (e.g. fire stations, parking spots) or mobile (e.g....
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StartPage 97
SubjectTerms Computer networks
Computer science
Computer systems organization -- Architectures -- Distributed architectures
Computing methodologies -- Modeling and simulation -- Simulation evaluation
Costs
Distributed computing
Distributed Matching
Event detection
Fires
Intelligent sensors
Mathematics of computing -- Mathematical analysis -- Mathematical optimization
Networks -- Network services -- Network management
Optimal matching
Resource management
Sensor Networks
Software and its engineering -- Software organization and properties -- Software system structures -- Distributed systems organizing principles
Theory of computation -- Design and analysis of algorithms -- Data structures design and analysis -- Pattern matching
Theory of computation -- Design and analysis of algorithms -- Mathematical optimization
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Title Distributed resource management and matching in sensor networks
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