Institutional Repository
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/06B38814-2483-404B-9B2A-1CEC22C98D80 | - |
| Identifier | https://doi.org/10.26233/heallink.tuc.65984 | - |
| Language | en | - |
| Extent | 71 pages | en |
| Title | Scaling geometric monitoring over distributed streams | en |
| Title | Κλιμάκωση της γεωμετρικής μεθόδου επί κατανεμημένων ροών δεδομένων | el |
| Creator | Keros Alexandros-Dimitrios | en |
| Creator | Κερος Αλεξανδρος-Δημητριος | el |
| Contributor [Thesis Supervisor] | Samoladas Vasilis | en |
| Contributor [Thesis Supervisor] | Σαμολαδας Βασιλης | el |
| Contributor [Committee Member] | Garofalakis Minos | en |
| Contributor [Committee Member] | Γαροφαλακης Μινως | el |
| Contributor [Committee Member] | Deligiannakis Antonios | en |
| Contributor [Committee Member] | Δεληγιαννακης Αντωνιος | el |
| Publisher | Πολυτεχνείο Κρήτης | el |
| Publisher | Technical University of Crete | en |
| Academic Unit | Technical University of Crete::School of Electrical and Computer Engineering | en |
| Academic Unit | Πολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών | el |
| Content Summary | Modern applications, such as telecommunication and sensor networks, have brought distributed data streams to the foreground, with monitoring tasks being an important aspect of such systems. The inefficiency of collecting data to a central point for processing dictates the need to devise local or semi-local algorithms that aim to reduce the communication overhead while retaining accuracy standards. The geometric monitoring method [Sharfman et al., “A Geometric Approach to Monitoring Threshold Functions over Distributed Data Streams”, ACM SIGMOD ’06 ICMD] provides a frame- work for enforcing local constraints at distributed nodes, as well as a method for resolving violations not representing the system’s state i.e., false alarms, in order to reduce the necessary communi- cation with the coordinating node. Furthermore, successive work proposed optimizations to the selection process of the nodes participating to the set that resolves such violations. We propose a heuristic method that exploits data stream characteristics and utilizes multi- objective optimization in order to avert, or delay, successive false alarms by optimally positioning vector representations of data streams during the violation resolution process. Additionally, a hierarchical node clustering method for deterministic and optimal node selection, found in [ Keren et al., “Geometric Monitoring of Heterogeneous Streams”, IEEE Trans. Knowl. Data Eng., 2014], is improved and simplified. Extensive experimentation on real-world and synthetic datasets showcase that the proposed methods can reduce the communication burden in half, compared to that of the original geometric monitoring method. | en |
| Type of Item | Διπλωματική Εργασία | el |
| Type of Item | Diploma Work | en |
| License | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en |
| Date of Item | 2016-07-07 | - |
| Date of Publication | 2016 | - |
| Subject | Data streams | en |
| Subject | Scalability | en |
| Subject | Distributed streams | en |
| Subject | Geometric monitoring | en |
| Subject | Multi-objective optimization | en |
| Bibliographic Citation | Alexandros-Dimitrios Keros, "Scaling geometric monitoring over distributed streams", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2016 | en |
| Bibliographic Citation | Αλέξανδρος-Δημήτριος Κέρος, "Κλιμάκωση της γεωμετρικής μεθόδου επί κατανεμημένων ροών δεδομένων", Διπλωματική Εργασία, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2016 | el |
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