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dc.contributor.authorAndreou, Panayiotis G.en
dc.contributor.authorZeinalipour-Yazdi, Constantinos D.en
dc.contributor.authorPamboris, Andreasen
dc.contributor.authorChrysanthis, Panos K.en
dc.contributor.authorSamaras, George S.en
dc.creatorAndreou, Panayiotis G.en
dc.creatorZeinalipour-Yazdi, Constantinos D.en
dc.creatorPamboris, Andreasen
dc.creatorChrysanthis, Panos K.en
dc.creatorSamaras, George S.en
dc.description.abstractIn order to process continuous queries over Wireless Sensor Networks (WSNs), sensors are typically organized in a Query Routing Tree (denoted as T) that provides each sensor with a path over which query results can be transmitted to the querying node. We found that current methods deployed in predominant data acquisition systems construct T in a sub-optimal manner which leads to significant waste of energy. In particular, since T is constructed in an ad hoc manner there is no guarantee that a given query workload will be distributed equally among all sensors. That leads to data collisions which represent a major source of energy waste. Additionally, current methods only provide a topological-based method, rather than a query-based method, to define the interval during which a sensing device should enable its transceiver in order to collect the query results from its children. We found that this imposes an order of magnitude increase in energy consumption. In this paper we present MicroPulse+, a novel framework for minimizing the consumption of energy during data acquisition in WSNs. MicroPulse+ continuously optimizes the operation of T by eliminating data transmission and data reception inefficiencies using a collection of in-network algorithms. In particular, MicroPulse+ introduces: (i) the Workload-Aware Routing Tree (WART) algorithm, which is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the critical path methoden
dc.description.abstractand (ii) the Energy-driven Tree Construction (ETC) algorithm, which balances the workload among nodes and minimizes data collisions. We show through micro-benchmarks on the CC2420 radio chip and trace-driven experimentation with real datasets from Intel Research and UC-Berkeley that MicroPulse+ provides significant energy reductions under a variety of conditions thus prolonging the longevity of a wireless sensor network. © 2010 Elsevier B.V. All rights reserved.en
dc.sourceInformation Systemsen
dc.subjectSensor networksen
dc.subjectSensor nodesen
dc.subjectWireless sensor networksen
dc.subjectEnergy consumptionen
dc.subjectData processingen
dc.subjectTrees (mathematics)en
dc.subjectData transmissionen
dc.subjectEnergy conversionen
dc.subjectQuery processingen
dc.subjectReal data setsen
dc.subjectContinuous queriesen
dc.subjectData acquisition systemen
dc.subjectEnergy reductionen
dc.subjectQuery routingen
dc.subjectQuerying nodesen
dc.subjectRadio chipsen
dc.subjectShow throughen
dc.subjectSource of energyen
dc.subjectTree constructionen
dc.subjectConsumption of energyen
dc.subjectSensing devicesen
dc.subjectEnergy utilizationen
dc.subjectCritical path methoden
dc.subjectData receptionen
dc.subjectNetwork algorithmsen
dc.subjectOrder of magnitudeen
dc.subjectQuery resultsen
dc.subjectQuery routing treesen
dc.subjectRouting treesen
dc.subjectTurnaround timeen
dc.titleOptimized query routing trees for wireless sensor networksen
dc.description.endingpage291 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied SciencesΤμήμα Πληροφορικής / Department of Computer Science
dc.description.notes<p>Cited By :20</p>en
dc.source.abbreviationInf Systen
dc.contributor.orcidZeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549]
dc.contributor.orcidAndreou, Panayiotis G. [0000-0002-6369-1094]
dc.contributor.orcidChrysanthis, Panos K. [0000-0001-7189-9816]

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