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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/8BE44719-274D-4498-9A19-2DB071C4694A | - |
| Identifier | https://dl.acm.org/citation.cfm?doid=2882903.2915225 | - |
| Identifier | https://doi.org/10.1145/2882903.2915225 | - |
| Language | en | - |
| Extent | 16 pages | en |
| Title | Scalable approximate query tracking over highly distributed data streams | 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 |
| Publisher | Association for Computing Machinery | 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 vN (compared to N for the original GM), where N is the number of sites in the network, to perform the monitoring process. Our experimental evaluation 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. | en |
| Type of Item | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Type of Item | Conference Full Paper | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2018-10-10 | - |
| Date of Publication | 2016 | - |
| Subject | GM | en |
| Subject | Geometric monitoring | en |
| Bibliographic Citation | N. Giatrakos, A. Deligiannakis and M. Garofalakis, "Scalable approximate query tracking over highly distributed data streams," in ACM SIGMOD International Conference on Management of Data, 2016, pp. 1497-1512. doi: 10.1145/2882903.2915225 | en |
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