dc.contributor.author | Zeinalipour-Yazdi, Constantinos D. | en |
dc.contributor.author | Andreou, Panayiotis G. | en |
dc.contributor.author | Chrysanthis, Panos K. | en |
dc.contributor.author | Samaras, George S. | en |
dc.contributor.author | Pitsillides, Andreas | en |
dc.creator | Zeinalipour-Yazdi, Constantinos D. | en |
dc.creator | Andreou, Panayiotis G. | en |
dc.creator | Chrysanthis, Panos K. | en |
dc.creator | Samaras, George S. | en |
dc.creator | Pitsillides, Andreas | en |
dc.date.accessioned | 2019-11-13T10:43:03Z | |
dc.date.available | 2019-11-13T10:43:03Z | |
dc.date.issued | 2007 | |
dc.identifier.isbn | 1-4244-1240-4 | |
dc.identifier.isbn | 978-1-4244-1240-2 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/55176 | |
dc.description.abstract | In this paper we present MicroPulse, a novel framework for adapting the waking window of a sensing device S based on the data workload incurred by a query Q. Assuming a typical tree-based aggregation scenario, the waking window is defined as the time interval ô during which S enables its transceiver in order to collect the results from its children. Minimizing the length of ô enables S to conserve energy that can be used to prolong the longevity of the network and hence the quality of results. Our method is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the Critical Path Method. We show through trace-driven experimentation with a real dataset that MicroPulse can reduce the energy cost of the waking window by three orders of magnitude. ©2007 IEEE. | en |
dc.source | Proceedings - IEEE International Conference on Mobile Data Management | en |
dc.source | 8th International Conference on Mobile Data Management, MDM 2007 | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-48649083322&doi=10.1109%2fMDM.2007.74&partnerID=40&md5=9e7c69d98addab5d0305b6458b2bea88 | |
dc.subject | Agglomeration | en |
dc.subject | Health | en |
dc.subject | Sensors | en |
dc.subject | Sensor networks | en |
dc.subject | Wireless sensor networks | en |
dc.subject | Telecommunication | en |
dc.subject | Scheduling | en |
dc.subject | Trees (mathematics) | en |
dc.subject | Data acquisition | en |
dc.subject | Energy conservation | en |
dc.subject | Data sets | en |
dc.subject | International conferences | en |
dc.subject | Management information systems | en |
dc.subject | Mobile data management | en |
dc.subject | Critical path method | en |
dc.subject | Turnaround time | en |
dc.subject | Windows | en |
dc.subject | Quality of results | en |
dc.subject | Conserve energy | en |
dc.subject | Energy costs | en |
dc.subject | Military operations | en |
dc.subject | Sugar (sucrose) | en |
dc.subject | Three orders of magnitude | en |
dc.subject | Time intervals | en |
dc.subject | Waking window | en |
dc.title | The micropulse framework for adaptive waking windows in sensor networks | en |
dc.type | info:eu-repo/semantics/conferenceObject | |
dc.identifier.doi | 10.1109/MDM.2007.74 | |
dc.description.startingpage | 351 | |
dc.description.endingpage | 355 | |
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 | Conference Object | en |
dc.description.notes | <p>Conference code: 72930 | en |
dc.description.notes | Cited By :7</p> | en |
dc.contributor.orcid | Pitsillides, Andreas [0000-0001-5072-2851] | |
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 | 0000-0001-5072-2851|0000-0002-8388-1549 | |
dc.gnosis.orcid | 0000-0002-6369-1094 | |
dc.gnosis.orcid | 0000-0001-7189-9816 | |