dc.contributor.author | Konstantinidis, Andreas | en |
dc.contributor.author | Zeinalipour-Yazdi, Constantinos D. | en |
dc.contributor.author | Andreou, Panayiotis G. | en |
dc.contributor.author | Samaras, George S. | en |
dc.contributor.author | Chrysanthis, Panos K. | en |
dc.creator | Konstantinidis, Andreas | en |
dc.creator | Zeinalipour-Yazdi, Constantinos D. | en |
dc.creator | Andreou, Panayiotis G. | en |
dc.creator | Samaras, George S. | en |
dc.creator | Chrysanthis, Panos K. | en |
dc.date.accessioned | 2019-11-13T10:40:46Z | |
dc.date.available | 2019-11-13T10:40:46Z | |
dc.date.issued | 2013 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/54286 | |
dc.description.abstract | Social communities of smartphone users have recently gained significant interest due to their wide social penetration. The applications in this domain, however, currently rely on centralized or cloud-like architectures for data sharing and searching tasks, introducing both data-disclosure and performance concerns. In this paper, we present a distributed search architecture for intelligent search of objects in a mobile social community. Our framework, coined SmartOpt, is founded on an in-situ data storage model, where captured objects remain local on smartphones and searches then take place over an intelligent multi-objective lookup structure we compute dynamically. Our MO-QRT structure optimizes several conflicting objectives, using a multi-objective evolutionary algorithm that calculates a diverse set of high quality non-dominated solutions in a single run. Then a decision-making subsystem is utilized to tune the retrieval preferences of the query user. We assess our ideas both using trace-driven experiments with mobility and social patterns derived by Microsoft's GeoLife project, DBLP and Pics 'n' Trails but also using our real Android SmartP2P (http://smartp2p.cs.ucy.ac.cy/) system deployed over our SmartLab (http://smartlab.cs.ucy.ac.cy/) testbed of 40+ smartphones. Our study reveals that SmartOpt yields high query recall rates of 95 %, with one order of magnitude less time and two orders of magnitude less energy than its competitors. © 2012 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-s2.0-84877813656&doi=10.1007%2fs10619-012-7108-0&partnerID=40&md5=b021ace07ba93ced9d02369af56550f8 | |
dc.subject | Social networks | en |
dc.subject | Multiobjective optimization | en |
dc.subject | Signal encoding | en |
dc.subject | Evolutionary algorithms | en |
dc.subject | Digital storage | en |
dc.subject | Smartphones | en |
dc.subject | Orders of magnitude | en |
dc.subject | Information management | en |
dc.subject | Conflicting objectives | en |
dc.subject | Multi-objective optimization | en |
dc.subject | Peer to peer | en |
dc.subject | Multi objective evolutionary algorithms | en |
dc.subject | Nondominated solutions | en |
dc.subject | Evolutionary computation | en |
dc.subject | Intelligent search | en |
dc.subject | Mobile social communities | en |
dc.title | Intelligent search in social communities of smartphone users | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1007/s10619-012-7108-0 | |
dc.description.volume | 31 | |
dc.description.issue | 2 | |
dc.description.startingpage | 115 | |
dc.description.endingpage | 149 | |
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 :4</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 | |