@article{MTMT:31858836,
	title = {Proactive, uncertainty-driven queries management at the edge},
	url = {https://m2.mtmt.hu/api/publication/31858836},
	author = {Kolomvatsos, Kostas and Anagnostopoulos, Christos},
	doi = {10.1016/j.future.2020.12.028},
	journal-iso = {FUTUR GENER COMP SYST},
	journal = {FUTURE GENERATION COMPUTER SYSTEMS},
	volume = {118},
	unique-id = {31858836},
	issn = {0167-739X},
	year = {2021},
	eissn = {1872-7115},
	pages = {75-93}
}

@inproceedings{MTMT:31140313,
	title = {Edge-Centric Queries’ Stream Management Based on an Ensemble Model},
	url = {https://m2.mtmt.hu/api/publication/31140313},
	author = {Kolomvatsos, Kostas and Anagnostopoulos, Christos},
	booktitle = {Advances in Integrations of Intelligent Methods},
	doi = {10.1007/978-981-15-1918-5_2},
	unique-id = {31140313},
	abstract = {The Internet of things (IoT) involves numerous devices that can interact with each other or with their environment to collect and process data. The collected data streams are guided to the cloud for further processing and the production of analytics. However, any processing in the cloud, even if it is supported by improved computational resources, suffers from an increased latency. The data should travel to the cloud infrastructure as well as the provided analytics back to end users or devices. For minimizing the latency, we can perform data processing at the edge of the network, i.e., at the edge nodes. The aim is to deliver analytics and build knowledge close to end users and devices minimizing the required time for realizing responses. Edge nodes are transformed into distributed processing points where analytics queries can be served. In this paper, we deal with the problem of allocating queries, defined for producing knowledge, to a number of edge nodes. The aim is to further reduce the latency by allocating queries to nodes that exhibit low load (the current and the estimated); thus, they can provide the final response in the minimum time. However, before the allocation, we should decide the computational burden that a query will cause. The allocation is concluded by the assistance of an ensemble similarity scheme responsible to deliver the complexity class for each query. The complexity class, thus, can be matched against the current load of every edge node. We discuss our scheme, and through a large set of simulations and the adoption of benchmarking queries, we reveal the potentials of the proposed model supported by numerical results.},
	year = {2020},
	pages = {27-48}
}

@CONFERENCE{MTMT:30346961,
	title = {An Edge-centric Ensemble Scheme for Queries Assignment},
	url = {https://m2.mtmt.hu/api/publication/30346961},
	author = {Kostas, Kolomvatsos and Christos, Anagnostopoulos},
	booktitle = {Proceedings of the 8th International Workshop on Combinations of Intelligent Methods and Applications co-located with 30th International Conference on Artificial Intelligence Tools (ICTAI 2018)},
	unique-id = {30346961},
	year = {2018},
	pages = {1-13}
}

@misc{MTMT:30346975,
	title = {An Empirical Study on the Usage of Conventions and Rules for SQL programming in FoSS},
	url = {https://m2.mtmt.hu/api/publication/30346975},
	author = {Papamichail, Aggelos},
	unique-id = {30346975},
	year = {2018}
}

@article{MTMT:32213913,
	title = {Estimating the Mixing Power of Business Logic and SQL Query Compiling Logic inside MVC Models},
	url = {https://m2.mtmt.hu/api/publication/32213913},
	author = {Aleksander, G. Maksimochkin},
	journal-iso = {IJSE},
	journal = {INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING},
	volume = {8},
	unique-id = {32213913},
	issn = {0974-3162},
	year = {2015},
	pages = {19-36}
}

@article{MTMT:26672434,
	title = {On Information System Architecture Supporting Acceptance Testing},
	url = {https://m2.mtmt.hu/api/publication/26672434},
	author = {Csaba, Szabó and Veronika, Szabóová},
	journal-iso = {EGYPTIAN COMP SCI J},
	journal = {EGYPTIAN COMPUTER SCIENCE JOURNAL},
	volume = {37},
	unique-id = {26672434},
	issn = {1110-2586},
	year = {2013},
	pages = {14-21}
}