4 citations · 7 across the 3 of their papers we have counts for
8 papers
Scheduling and Communication Schemes for Decentralized Federated Learning
Bahaa-Eldin Ali Abdelghany, Ana Fernández-Vilas, Manuel Fernández-Veiga +3
Federated learning (FL) is a distributed machine learning paradigm in which a large number of clients coordinate with a central server to learn a model without sharing their own tr…
Using Decentralized Aggregation for Federated Learning with Differential Privacy
Hadeel Abd El-Kareem, Abd El-Moaty Saleh, Ana Fernández-Vilas +2
Nowadays, the ubiquitous usage of mobile devices and networks have raised concerns about the loss of control over personal data and research advance towards the trade-off between p…
Energy Efficient Power and Channel Allocation in Underlay Device to Multi Device Communications
Mariem Hmila, Manuel Fernández-Veiga, Miguel Rodríguez-Pérez +1
In this paper, we optimize the energy efficiency (bits/s/Hz/J) of device-to-multi-device (D2MD) wireless communications. While the device-to-device scenario has been extensively st…
Dynamic EEE Coalescing: Techniques and Bounds
Sergio Herrería-Alonso, Miguel Rodríguez-Pérez, Manuel Fernández-Veiga +1
Frame coalescing is one of the most efficient techniques to manage the low power idle (LPI) mode supported by Energy Efficient Ethernet (EEE) interfaces. This technique enables EEE…
Implementing energy saving algorithms for Ethernet link aggregates with ONOS
Pablo Fondo Ferreiro, Miguel Rodríguez Pérez, Manuel Fernández Veiga
During the last few years, there has been plenty of research for reducing energy consumption in telecommunication infrastructure. However, many of the proposals remain unim-plement…
QoS-aware Energy-Efficient Algorithms for Ethernet Link Aggregates in Software-Defined Networks
Pablo Fondo Ferreiro, Miguel Rodríguez Pérez, Manuel Fernández Veiga
In this paper we discuss the implementation of an ONOS application that leverages Energy-Efficient Ethernet links between a pair of switches and shares incoming traffic among the l…