Complex event recognition in the Big Data era: a survey

Επιστημονική δημοσίευση - Άρθρο Περιοδικού uoadl:3071289 20 Αναγνώσεις

Μονάδα:
Ερευνητικό υλικό ΕΚΠΑ
Τίτλος:
Complex event recognition in the Big Data era: a survey
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
The concept of event processing is established as a generic computational paradigm in various application fields. Events report on state changes of a system and its environment. Complex event recognition (CER) refers to the identification of composite events of interest, which are collections of simple, derived events that satisfy some pattern, thereby providing the opportunity for reactive and proactive measures. Examples include the recognition of anomalies in maritime surveillance, electronic fraud, cardiac arrhythmias and epidemic spread. This survey elaborates on the whole pipeline from the time CER queries are expressed in the most prominent languages, to algorithmic toolkits for scaling-out CER to clustered and geo-distributed architectural settings. We also highlight future research directions. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
Έτος δημοσίευσης:
2020
Συγγραφείς:
Giatrakos, N.
Alevizos, E.
Artikis, A.
Deligiannakis, A.
Garofalakis, M.
Περιοδικό:
The VLDB Journal
Εκδότης:
Springer-Verlag
Τόμος:
29
Αριθμός / τεύχος:
1
Σελίδες:
313-352
Λέξεις-κλειδιά:
Algorithmic languages; Elasticity; Surveys, Cardiac arrhythmia; Complex events; Computational paradigm; Distributed processing; Future research directions; Maritime surveillance; Parallelism; Proactive measures, Big data
Επίσημο URL (Εκδότης):
DOI:
10.1007/s00778-019-00557-w
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