Institutional Repository
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/A16D0308-EF61-468D-8B05-3162D819231B | - |
| Identifier | https://doi.org/10.1016/j.is.2018.05.001 | - |
| Identifier | https://www.sciencedirect.com/science/article/pii/S0306437918300322 | - |
| Language | en | - |
| Extent | 29 pages | en |
| Title | Scalable approximate query tracking over highly distributed data streams with tunable accuracy guarantees | en |
| Creator | Giatrakos Nikolaos | en |
| Creator | Γιατρακος Νικολαος | el |
| Creator | Deligiannakis Antonios | en |
| Creator | Δεληγιαννακης Αντωνιος | el |
| Creator | Garofalakis Minos | en |
| Creator | Γαροφαλακης Μινως | el |
| Creator | Keren Daniel | en |
| Creator | Samoladas Vasilis | en |
| Creator | Σαμολαδας Βασιλης | el |
| Publisher | Elsevier | en |
| Content Summary | 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 |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2019-09-03 | - |
| Date of Publication | 2018 | - |
| Subject | Data streams | en |
| Subject | Distributed function tracking | en |
| Subject | Sampling | en |
| Bibliographic Citation | 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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