Searched for: author%3A%22Mhaisen%2C+N.%22
(1 - 7 of 7)
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Zheng, Jingjing (author), Li, Kai (author), Mhaisen, N. (author), Ni, Wei (author), Tovar, Eduardo (author), Guizani, Mohsen (author)
Federated learning (FL) is increasingly considered to circumvent the disclosure of private data in mobile edge computing (MEC) systems. Training with large data can enhance FL learning accuracy, which is associated with non-negligible energy use. Scheduled edge devices with small data save energy but decrease FL learning accuracy due to a...
conference paper 2023
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Mhaisen, N. (author), Sinha, Abhishek (author), Paschos, Georgios (author), Iosifidis, G. (author)
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. The successive file requests are assumed to be generated by an adversary, and no assumption is made on the accuracy of the oracle. We provide a...
journal article 2023
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Abdellatif, Alaa Awad (author), Mhaisen, N. (author), Mohamed, Amr (author), Erbad, Aiman (author), Guizani, Mohsen (author)
The rise of chronic disease patients and the pandemic pose immediate threats to healthcare expenditure and mortality rates. This calls for transforming healthcare systems away from one-on-one patient treatment into intelligent health systems, leveraging the recent advances of Internet of Things and smart sensors. Meanwhile, reinforcement...
journal article 2023
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Mhaisen, N. (author), Allahham, Mhd Saria (author), Mohamed, Amr (author), Erbad, Aiman (author), Guizani, Mohsen (author)
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 Smart Contracts (SCs) to add trust and transparency to their criteria. However, deploying...
journal article 2022
document
Zheng, Jingjing (author), Li, Kai (author), Mhaisen, N. (author), Ni, Wei (author), Tovar, Eduardo (author), Guizani, Mohsen (author)
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 selecting the IoT devices with large data sets for training, which gives rise to a higher energy...
journal article 2022
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Mhaisen, N. (author), Iosifidis, G. (author), Leith, Douglas (author)
The design of effective online caching policies is an increasingly important problem for content distribution networks, online social networks and edge computing services, among other areas. This paper proposes a new algorithmic toolbox for tackling this problem through the lens of optimistic online learning. We build upon the Follow-the...
conference paper 2022
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Baccour, Emna (author), Mhaisen, N. (author), Abdellatif, Alaa Awad (author), Erbad, Aiman (author), Mohamed, Amr (author), Hamdi, Mounir (author), Guizani, Mohsen (author)
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems and speech processing applications to robotics control and military surveillance. This is driven by the easier access to sensory data and the enormous scale of pervasive...
journal article 2022
Searched for: author%3A%22Mhaisen%2C+N.%22
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