@inproceedings{487100a2762947e0b226103e3cb69292,
title = "A heuristically optimized complex event processing engine for big data stream analytics",
abstract = "This paper describes a Big Data stream analytics platform developed within the DEWI project for processing upcoming events from wireless sensors installed in a truck. The platform consists of a Complex Event Processing (CEP) engine capable of triggering alarms from a predefined set of rules. In general these rules are characterized by multiple parameters, for which finding their optimal value usually yields a challenging task. In this paper we explain a methodology based on a meta-heuristic solver that is used as a wrapper to obtain optimal parametric rules for the CEP engine. In particular this approach optimizes CEP rules through the refinement of the parameters controlling their behavior based on an alarm detection improvement criterion. As a result the proposed scheme retrieves the rules parameterized in a detectionoptimal fashion. Results for a certain use case – i.e. fuel level of the vehicle – are discussed towards assessing the performance gains provided by our method.",
keywords = "Big data, Complex event processing, Optimization",
author = "Olabarrieta, {Ignacio I{\~n}aki} and Torre-Bastida, {Ana I.} and Ibai La{\~n}a and Sergio Campos-Cordobes and {Del Ser}, Javier",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2017.; Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 ; Conference date: 22-02-2017 Through 24-02-2017",
year = "2017",
doi = "10.1007/978-981-10-3728-3_11",
language = "English",
isbn = "9789811037276",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "101--111",
editor = "{Del Ser}, Javier",
booktitle = "Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017)",
address = "Germany",
}