Distributed Alarming in the On-Duty and Off-Duty Models

Decentralized monitoring and alarming systems can be an attractive alternative to centralized architectures. Distributed sensor nodes (e.g., in the smart grid's distribution network) are closer to an observed event than a global and remote observer or controller. This improves the visibility an...

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Veröffentlicht in:IEEE/ACM transactions on networking Jg. 24; H. 1; S. 218 - 230
Hauptverfasser: Bienkowski, Marcin, Gasieniec, Leszek, Klonowski, Marek, Korzeniowski, Miroslaw, Mans, Bernard, Schmid, Stefan, Wattenhofer, Roger
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.02.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1063-6692, 1558-2566
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Abstract Decentralized monitoring and alarming systems can be an attractive alternative to centralized architectures. Distributed sensor nodes (e.g., in the smart grid's distribution network) are closer to an observed event than a global and remote observer or controller. This improves the visibility and response time of the system. Moreover, in a distributed system, local problems may also be handled locally and without overloading the communication network. This paper studies alarming from a distributed computing perspective and for two fundamentally different scenarios: on-duty and off-duty. We model the alarming system as a sensor network consisting of a set of distributed nodes performing local measurements to sense events. In order to avoid false alarms, the sensor nodes cooperate and only escalate an event (i.e., raise an alarm) if the number of sensor nodes sensing an event exceeds a certain threshold. In the on-duty scenario, nodes not affected by the event can actively help in the communication process, while in the off-duty scenario, non-event nodes are inactive. We present and analyze algorithms that minimize the reaction time of the monitoring system while avoiding unnecessary message transmissions. We investigate time and message complexity tradeoffs in different settings, and also shed light on the optimality of our algorithms by deriving cost lower bounds for distributed alarming systems.
AbstractList Decentralized monitoring and alarming systems can be an attractive alternative to centralized architectures. Distributed sensor nodes (e.g., in the smart grid's distribution network) are closer to an observed event than a global and remote observer or controller. This improves the visibility and response time of the system. Moreover, in a distributed system, local problems may also be handled locally and without overloading the communication network. This paper studies alarming from a distributed computing perspective and for two fundamentally different scenarios: on-duty and off-duty. We model the alarming system as a sensor network consisting of a set of distributed nodes performing local measurements to sense events. In order to avoid false alarms, the sensor nodes cooperate and only escalate an event (i.e., raise an alarm) if the number of sensor nodes sensing an event exceeds a certain threshold. In the on-duty scenario, nodes not affected by the event can actively help in the communication process, while in the off-duty scenario, non-event nodes are inactive. We present and analyze algorithms that minimize the reaction time of the monitoring system while avoiding unnecessary message transmissions. We investigate time and message complexity tradeoffs in different settings, and also shed light on the optimality of our algorithms by deriving cost lower bounds for distributed alarming systems.
Author Klonowski, Marek
Mans, Bernard
Gasieniec, Leszek
Korzeniowski, Miroslaw
Schmid, Stefan
Bienkowski, Marcin
Wattenhofer, Roger
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Snippet Decentralized monitoring and alarming systems can be an attractive alternative to centralized architectures. Distributed sensor nodes (e.g., in the smart...
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SubjectTerms Algorithms
Complexity theory
Computational modeling
Context
Disaster detection
Distributed algorithms
distributed coordination
Monitoring
neighborhood covers
output-sensitive algorithms
Runtime
Schedules
sensor networks
Sensors
Title Distributed Alarming in the On-Duty and Off-Duty Models
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