dc.contributor.author | Andreou, Panayiotis G. | en |
dc.contributor.author | Zeinalipour-Yazdi, Constantinos D. | en |
dc.contributor.author | Chrysanthis, Panos K. | en |
dc.contributor.author | Samaras, George S. | en |
dc.creator | Andreou, Panayiotis G. | en |
dc.creator | Zeinalipour-Yazdi, Constantinos D. | en |
dc.creator | Chrysanthis, Panos K. | en |
dc.creator | Samaras, George S. | en |
dc.date.accessioned | 2019-11-13T10:38:15Z | |
dc.date.available | 2019-11-13T10:38:15Z | |
dc.date.issued | 2011 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/53526 | |
dc.description.abstract | In this paper, we present an innovative framework for efficiently monitoring Wireless Sensor Networks (WSNs). Our framework, coined KSpot, utilizes a novel top-k query processing algorithm we developed, in conjunction with the concept of in-network views, in order to minimize the cost of query execution. For ease of exposition, consider a set of sensors acquiring data from their environment at a given time instance. The generated information can conceptually be thought as a horizontally fragmented base relation R. Furthermore, the results to a user-defined query Q, registered at some sink point, can conceptually be thought as a view V. Maintaining consistency between V and R is very expensive in terms of communication and energy. Thus, KSpot focuses on a subset V′(⊆V) that unveils only the k highest-ranked answers at the sink, for some user defined parameter k. To illustrate the efficiency of our framework, we have implemented a real system in nesC, which combines the traditional advantages of declarative acquisition frameworks, like TinyDB, with the ideas presented in this work. Extensive real-world testing and experimentation with traces from UC-Berkeley, the University of Washington and Intel Research Berkeley, show that KSpot provides an up to 66% of energy savings compared to TinyDB, minimizes both the size and number of packets transmitted over the network (up to 77%), and prolongs the longevity of a WSN deployment to new scales. © 2010 Springer Science+Business Media, LLC. | en |
dc.source | Distributed and Parallel Databases | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650889013&doi=10.1007%2fs10619-010-7072-5&partnerID=40&md5=765bb3080ae5d07c8840575d27169b91 | |
dc.subject | Information retrieval | en |
dc.subject | Sensor networks | en |
dc.subject | Wireless sensor networks | en |
dc.subject | Energy saving | en |
dc.subject | Real systems | en |
dc.subject | Query processing | en |
dc.subject | In-network aggregation | en |
dc.subject | Power efficiency | en |
dc.subject | Query execution | en |
dc.subject | Real-world testing | en |
dc.subject | Time instances | en |
dc.subject | Top-k query processing | en |
dc.subject | University of Washington | en |
dc.subject | User-defined parameters | en |
dc.title | Power efficiency through tuple ranking in wireless sensor network monitoring | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1007/s10619-010-7072-5 | |
dc.description.volume | 29 | |
dc.description.issue | 1-2 | |
dc.description.startingpage | 113 | |
dc.description.endingpage | 150 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Cited By :6</p> | en |
dc.source.abbreviation | Distrib Parallel Databases | en |
dc.contributor.orcid | Zeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549] | |
dc.contributor.orcid | Andreou, Panayiotis G. [0000-0002-6369-1094] | |
dc.contributor.orcid | Chrysanthis, Panos K. [0000-0001-7189-9816] | |
dc.gnosis.orcid | 0000-0002-8388-1549 | |
dc.gnosis.orcid | 0000-0002-6369-1094 | |
dc.gnosis.orcid | 0000-0001-7189-9816 | |