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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Moura, J. (2023). Decentralized control orchestration for dynamic edge programmable systems. In 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME). Tenerife, Canary Islands, Spain: IEEE.
Exportar Referência (IEEE) 
J. A. Moura,  "Decentralized control orchestration for dynamic edge programmable systems", in 2023 3rd Int. Conf. on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Tenerife, Canary Islands, Spain, IEEE, 2023
Exportar BibTeX 
@inproceedings{moura2023_1734973946501,
	author = "Moura, J.",
	title = "Decentralized control orchestration for dynamic edge programmable systems",
	booktitle = "2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)",
	year = "2023",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/ICECCME57830.2023.10252983",
	publisher = "IEEE",
	address = "Tenerife, Canary Islands, Spain",
	organization = "",
	url = "https://ieeexplore.ieee.org/xpl/conhome/10252163/proceeding"
}
Exportar RIS 
TY  - CPAPER
TI  - Decentralized control orchestration for dynamic edge programmable systems
T2  - 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
AU  - Moura, J.
PY  - 2023
DO  - 10.1109/ICECCME57830.2023.10252983
CY  - Tenerife, Canary Islands, Spain
UR  - https://ieeexplore.ieee.org/xpl/conhome/10252163/proceeding
AB  - There is an increasingly focus on Programmable Systems for controlling edge networked systems. During the normal operation of these systems a high number of unpredicted new flows can be suddenly presented to the system control level, requesting novel flow rules to successfully steer the associated data toward their final destinations. The extra control required by these new flows can increase the channel control workload up to a level, the available active controllers are not able to process that workload in a satisfactory degree. The current work investigates a distributed solution, which online acquires the control channel workload and adjusts the number of active controllers to variations on that measured workload. The controller scaling provides an elastic and efficient control plane for dynamic edge programmable systems. Thus, our work discusses the design, deployment and evaluation of the proposed framework. The obtained experimental results validate the main objectives of the multicast-based decentralized and scalable control orchestration, which positively accommodates the unexpected changes on the number of new data flows traversing the controlled edge network infrastructure, using only minimal information shared among controllers and diminishing the control channel workload.
ER  -