2007
DOI: 10.1109/tmc.2007.1009
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Communication and Coordination in Wireless Sensor and Actor Networks

Abstract: Abstract-In this paper, coordination and communication problems in Wireless Sensor and Actor Networks (WSANs) are jointly addressed in a unifying framework. A sensor-actor coordination model is proposed based on an event-driven partitioning paradigm. Sensors are partitioned into different sets, and each set is constituted by a data-delivery tree associated with a different actor. The optimal solution for the partitioning strategy is determined by mathematical programming, and a distributed solution is proposed… Show more

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Cited by 194 publications
(100 citation statements)
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“…The concepts of sensor-actor coordination and actor-actor coordination were introduced, and centralized optimal solutions and distributed heuristics were proposed. However, many challenging applications require support for mobile actors, which is not provided in [8]. Hence, in this paper, we extend our previous work in several directions.…”
Section: Introductionmentioning
confidence: 88%
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“…The concepts of sensor-actor coordination and actor-actor coordination were introduced, and centralized optimal solutions and distributed heuristics were proposed. However, many challenging applications require support for mobile actors, which is not provided in [8]. Hence, in this paper, we extend our previous work in several directions.…”
Section: Introductionmentioning
confidence: 88%
“…In line with recent work on routing algorithms for sensor networks [8], [11], [12], [19], we study the sensor-actor coordination based on a geographical routing paradigm. Geographical routing algorithms are attractive especially for their scalability since routing decisions are inherently localized [19].…”
Section: Location Managementmentioning
confidence: 99%
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“…The Rodin platform is an open and extensible tool for Event-B specification and verification [3,18]. It contains a database of modeling elements used for constructing system models such as …”
Section: Fig1 Machine and Context Relationshipmentioning
confidence: 99%