Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Naram Mhaisen"'
Autor:
Naram Mhaisen, Qutaibah M. Malluhi
Publikováno v:
IEEE Access, Vol 8, Pp 164977-164986 (2020)
Multi-cloud storage systems are becoming more popular due to the ever-expanding amount of consumer data. This growth is accompanied by increasing concerns regarding security, privacy, and reliability of cloud storage solutions. Ensuring data consiste
Externí odkaz:
https://doaj.org/article/ed0734615d7340f4b851fe5d2e736451
Publikováno v:
Alexandria Engineering Journal, Vol 58, Iss 4, Pp 1291-1300 (2019)
Battery Energy Storage Systems (BESSs) are an integral part of a sustainable and resilient smart grid. The security of such critical cyber-physical infrastructure is considered as a major priority for both industry and academia. In this paper, we pro
Externí odkaz:
https://doaj.org/article/a0c1f238ee6a48f790ca3685a75410d3
Publikováno v:
Proceedings of the ACM on Measurement and Analysis of Computing Systems. 6:1-28
We take a systematic look at the problem of storing whole files in a cache with limited capacity in the context of optimistic learning, where the caching policy has access to a prediction oracle (provided by, e.g., a Neural Network). The successive f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7dac721037324aff6c540409a7eabe0c
https://doi.org/10.1145/3570608
https://doi.org/10.1145/3570608
Publikováno v:
IEEE Internet of Things Journal. 9:21099-21110
Federated learning (FL) has been increasingly considered to preserve data training privacy from eavesdropping attacks in mobile-edge computing-based Internet of Things (EdgeIoT). On the one hand, the learning accuracy of FL can be improved by selecti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::544ce0df8b3dfcccb6347937f9ad0f19
https://doi.org/10.1109/jiot.2022.3176739
https://doi.org/10.1109/jiot.2022.3176739
Autor:
Mhd Saria Allahham, Alaa Awad Abdellatif, Naram Mhaisen, Amr Mohamed, Aiman Erbad, Mohsen Guizani
Publikováno v:
IEEE Transactions on Cognitive Communications and Networking. 8:1287-1300
The rapid production of mobile devices along with the wireless applications boom is continuing to evolve daily. This motivates the exploitation of wireless spectrum using multiple Radio Access Technologies (multi-RAT) and developing innovative networ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60128728de9d48497505312df3e9b82b
https://doi.org/10.1109/tccn.2022.3155727
https://doi.org/10.1109/tccn.2022.3155727
Publikováno v:
2023 IEEE Wireless Communications and Networking Conference (WCNC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b908c5493adab4f6843062c8e2789120
https://doi.org/10.1109/wcnc55385.2023.10118940
https://doi.org/10.1109/wcnc55385.2023.10118940
Publikováno v:
IEEE Transactions on Network Science and Engineering. 9:401-415
Service provisioning systems assign users to service providers according to allocation criteria that strike an optimal trade-off between users Quality of Experience (QoE) and the operation cost endured by providers. These systems have been leveraging
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06dd01a30feb03d6a9082b2640ea3b3b
https://doi.org/10.1109/tnse.2021.3118970
https://doi.org/10.1109/tnse.2021.3118970
Publikováno v:
IEEE Transactions on Network Science and Engineering. 9:55-66
Distributed learning algorithms aim to leverage distributed and diverse data stored at users' devices to learn a global phenomena by performing training amongst participating devices and periodically aggregating their local models' parameters into a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b04224d3599a3ac6555bf3fdfed6ff7d
https://doi.org/10.1109/tnse.2021.3053588
https://doi.org/10.1109/tnse.2021.3053588
Autor:
Emna Baccour, Naram Mhaisen, Alaa Awad Abdellatif, Aiman Erbad, Amr Mohamed, Mounir Hamdi, Mohsen Guizani
Publikováno v:
IEEE Communications Surveys and Tutorials. 24(4)
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems to robotics control and military surveillance. This is driven by the easier
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33cb802268b369140e447525bf1c3241
http://resolver.tudelft.nl/uuid:430746a5-76e0-4571-803d-a05e0b670ae9
http://resolver.tudelft.nl/uuid:430746a5-76e0-4571-803d-a05e0b670ae9
Autor:
Gramaglia, Marco, Naram Mhaisen, Garcia-Saavedra, Andres, Garcia, Gines, Chang, Chia-Yu, De Vleeschauwer, Danny, Molina, Maria, Slamnik-Krijestorac, Nina, Soto, Paola, Camelo, Miguel, Fuentes, Lidia, Amor, Mercedes, Pinto, Monica, Ca��ete, ��ngel, Munoz, Daniel-Jesus, Fiore, Marco, Gucciardo, Michele, Lutu, Andra
This deliverable presents DAEMON���s initial view on the problem of real-time control and network functions intelligence. The work presented in this document tackles two main points: ��� Understanding what the main challenges from the arc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e291f6f1614440f98d8dbc322b54f44
