2013
DOI: 10.1016/j.comcom.2012.11.003
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Auctions and iMesh based task assignment in wireless sensor and actuator networks

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Cited by 25 publications
(13 citation statements)
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“…The next round starts with decision making process, where each robot is responsible for handling events reported to it, and negotiates with other robots about the task assignment. Our event reporting scheme replaces quorum based search (used in [3]) with iMesh structure [21], and also adds an auction in robot network in a similar way as in [23] to further improve the selection. We use two different means of communication in order to achieve our goal; namely, lowpower (low-range) communication for sensor-sensor or sensor-robot transmissions, and higher-power (higher-range) communication for robot-robot transmissions.…”
Section: Distributed Dispatch (Mad and Mar)mentioning
confidence: 99%
“…The next round starts with decision making process, where each robot is responsible for handling events reported to it, and negotiates with other robots about the task assignment. Our event reporting scheme replaces quorum based search (used in [3]) with iMesh structure [21], and also adds an auction in robot network in a similar way as in [23] to further improve the selection. We use two different means of communication in order to achieve our goal; namely, lowpower (low-range) communication for sensor-sensor or sensor-robot transmissions, and higher-power (higher-range) communication for robot-robot transmissions.…”
Section: Distributed Dispatch (Mad and Mar)mentioning
confidence: 99%
“…Auction-based [104] Behavior-based [105] Event prediction [106] that the network maintained the required transfer rate (19 Kbps for the proposed application) throughout the network's lifetime. This setup is similar to that which was used in [90].…”
Section: Path Planningmentioning
confidence: 99%
“…Auction-based task allocation is studied in [104] by using auctions to improve the recent information mesh (iMesh) based distance sensitive service discovery approach. The idea was to improve on iMesh's ability to find the closest service 95% of the time.…”
Section: Task Allocationmentioning
confidence: 99%
“…The most popular approach in the literature involves random deployment of the actors that remain static and move only when a target is reported [10][11][12]. In [13] the deployment of actors was managed by using an algorithm, which generates a connected pseudo-random unit graphs. The aim of this algorithm is to distribute the actors uniformly in the monitored area, while maintaining their connectivity.…”
Section: Control Of Actors' Mobilitymentioning
confidence: 99%