Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Jorge Martin-Perez"'
Autor:
Jorge Martin-Perez, Koteswararao Kondepu, Danny De Vleeschauwer, Venkatarami Reddy, Carlos Guimaraes, Andrea Sgambelluri, Luca Valcarenghi, Chrysa Papagianni, Carlos J. Bernardos
Publikováno v:
IEEE Access, Vol 10, Pp 9587-9602 (2022)
With the increasing adoption of intelligent transportation systems and the upcoming era of autonomous vehicles, vehicular services (such as remote driving, cooperative awareness, and hazard warning) will have to operate in an ever-changing and dynami
Externí odkaz:
https://doaj.org/article/87b9f195dd814f9698073e2834414af8
Autor:
Milan Groshev, Jorge Martin-Perez, Carlos Guimaraes, Antonio de la Oliva, Carlos J. Bernardos
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
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Wireless communications represent a game changer for future manufacturing plants, enabling flexible production chains as machinery and other components are not restricted to a location by the rigid wired connections on the factory floor. However, the
Autor:
Milan Groshev, Jorge Martin-Perez, Francesco Malandrino, Carla-Fabiana Chiasserini, Carlos J. Bernardos
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
IEEE/ACM transactions on networking (Online) (2021).
info:cnr-pdr/source/autori:Jorge Martin Perez; Francesco Malandrino; Carla Fabiana Chiasserini; Milan Groshev; Carlos Bernardos/titolo:KPI Guarantees in Network Slicing/doi:/rivista:IEEE%2FACM transactions on networking (Online)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
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IEEE/ACM transactions on networking (Online) (2021).
info:cnr-pdr/source/autori:Jorge Martin Perez; Francesco Malandrino; Carla Fabiana Chiasserini; Milan Groshev; Carlos Bernardos/titolo:KPI Guarantees in Network Slicing/doi:/rivista:IEEE%2FACM transactions on networking (Online)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
Thanks to network slicing, mobile networks can now support multiple and diverse services, each requiring different key performance indicators (KPIs). In this new scenario, it is critical to allocate network and computing resources efficiently and in
Autor:
Josep Mangues-Bafalluy, Corrado Puligheddu, Jorge Martin-Perez, Andrea Sgambelluri, Koen A.E. De Schepper, Engin Zeydan, Carla-Fabiana Chiasserini, Luca Valcarenghi, Sokratis Barmpounakis, Panagiotis Kontopoulos, Francesco Paolucci, Xi Li, Nikolaos Koursioumpas, Carlos J. Bernardos, Andres Garcia-Saavedra, Ricardo Martinez, Carlos Guimaraes, Kiril Antevski, Lina Magoula, Jorge Baranda, Danny De Vleeschauwer, Claudio EttoreCasetti, Chrysa Papagianni
Publikováno v:
Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning
Meeting 5G high bandwidth rates, ultra‐low latencies, and high reliabilities requires of network infrastructures that automatically increase/decrease the resources based on their customers' demand.An autonomous and dynamic management of a 5G networ
Autor:
Luigi Girletti, Jorge Martin-Perez, Abdulrahman Algunayah, Paola Soto, Francesc Wilhelmi, K Venkat Ramnan, Mohammad Alfaifi, David Góez, Ramon Vallés, Boris Bellalta, Rajasekar Mohan
Publikováno v:
ITU Journal on Future and Evolving Technologies
With the advent of Artificial Intelligence (AI)-empowered communications, industry, academia, and standardization organizations are progressing on the definition of mechanisms and procedures to address the increasing complexity of future 5G and beyon
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
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This paper proposes a dynamic pricing and revenue-driven service federation strategy based on a Deep Q-Network (DQN) to instantly and automatically decide federation across different service provider domains, each introduces dynamic service prices of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f33a8e9106298b7a6c71d96430d0194d
https://hdl.handle.net/10016/33964
https://hdl.handle.net/10016/33964
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
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Industry 4.0 aims to support smarter and autonomous processes while improving agility, cost efficiency, and user experience. To fulfill its promises, properly processing the data of the industrial processes and infrastructures is required. Artificial
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ee78156cccadde3fe5e30477f2ab955
https://hdl.handle.net/10016/33912
https://hdl.handle.net/10016/33912
Autor:
Jorge, Martin-Perez, Kiril, Antevski, Carlos, Guimaraes, Bernardos, C. J., Chrysa, Papagianni, Danny de Vleeschauwe, Lina, Magoula, Sokratis, Barmpounakis, Panagiotis, Kontopoulos, Nikolaos, Koursioumpas, Andrea, Sgambelluri, Francesco, Paolucci, Luca, Valcarenghi, Andres, Garcia-Saavedra, Xi, Li, Puligheddu, Corrado, Chiasserini, Carla Fabiana, Casetti, CLAUDIO ETTORE, Mangues-Bafalluy, J., Martínez, J. Baranda R., Engin, Zeydan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2153::04d68f945efc0750082c26dcc2e74650
http://hdl.handle.net/11583/2863452
http://hdl.handle.net/11583/2863452
Autor:
Jorge Martin-Perez, Balazs Nemeth, Antonio de la Oliva, Nuria Molner, Carlos J. Bernardos, Balazs Sonkoly
Publikováno v:
e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
IEEE Transactions on Mobile Computing
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
Universidad Carlos III de Madrid (UC3M)
IEEE Transactions on Mobile Computing
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
The ongoing research and industrial exploitation of SDN and NFV technologies promise higher flexibility on network automation and infrastructure optimization. Choosing the location of Virtual Network Functions is a central problem in the automation a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e162edd36228d93c7b370504239816c
https://doi.org/10.1109/TMC.2021.3055426
https://doi.org/10.1109/TMC.2021.3055426
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
instname
Edge & Fog computing have received considerable attention as promising candidates for the evolution of robotic systems. In this letter, we propose COTORRA, an Edge & Fog driven robotic testbed that combines context information with robot sensor data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1a3e1ba32281b0e45e86710909ed37f
http://hdl.handle.net/10016/33937
http://hdl.handle.net/10016/33937