Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/A16D0308-EF61-468D-8B05-3162D819231B | - |
| Αναγνωριστικό | https://doi.org/10.1016/j.is.2018.05.001 | - |
| Αναγνωριστικό | https://www.sciencedirect.com/science/article/pii/S0306437918300322 | - |
| Γλώσσα | en | - |
| Μέγεθος | 29 pages | en |
| Τίτλος | Scalable approximate query tracking over highly distributed data streams with tunable accuracy guarantees | en |
| Δημιουργός | Giatrakos Nikolaos | en |
| Δημιουργός | Γιατρακος Νικολαος | el |
| Δημιουργός | Deligiannakis Antonios | en |
| Δημιουργός | Δεληγιαννακης Αντωνιος | el |
| Δημιουργός | Garofalakis Minos | en |
| Δημιουργός | Γαροφαλακης Μινως | el |
| Δημιουργός | Keren Daniel | en |
| Δημιουργός | Samoladas Vasilis | en |
| Δημιουργός | Σαμολαδας Βασιλης | el |
| Εκδότης | Elsevier | en |
| Περίληψη | The recently proposed Geometric Monitoring (GM) method has provided a general tool for the distributed monitoring of arbitrary non-linear queries over streaming data observed by a collection of remote sites, with numerous practical applications. Unfortunately, GM-based techniques can suffer from serious scalability issues with increasing numbers of remote sites. In this paper, we propose novel techniques that effectively tackle the aforementioned scalability problems by exploiting a carefully designed sample of the remote sites for efficient approximate query tracking. Our novel sampling-based scheme utilizes a sample of cardinality proportional to N (compared to N for the original GM and its variants), where N is the number of sites in the network, to perform the monitoring process. Our extensive experimental evaluation and comparative analysis over a variety of real-life data streams demonstrates that our sampling-based techniques can significantly reduce the communication cost during distributed monitoring with controllable, predefined accuracy guarantees. In that, we manage to scale the monitoring of any given non-linear function on much higher network scales which had not been reached by any GM related method or variant so far. | en |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2019-09-03 | - |
| Ημερομηνία Δημοσίευσης | 2018 | - |
| Θεματική Κατηγορία | Data streams | en |
| Θεματική Κατηγορία | Distributed function tracking | en |
| Θεματική Κατηγορία | Sampling | en |
| Βιβλιογραφική Αναφορά | N. Giatrakos, A. Deligiannakis, M. Garofalakis, D. Keren and V. Samoladas, "Scalable approximate query tracking over highly distributed data streams with tunable accuracy guarantees," Inf. Syst., vol. 76, pp. 59-87, Jul. 2018. doi: 10.1016/j.is.2018.05.001 | en |
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