[HTML][HTML] A review of advanced localization techniques for crowdsensing wireless sensor networks

A Coluccia, A Fascista - Sensors, 2019 - mdpi.com
The wide availability of sensing modules and computing capabilities in modern mobile
devices (smartphones, smart watches, in-vehicle sensors, etc.) is driving the shift from mote …

DeepCog: Cognitive network management in sliced 5G networks with deep learning

D Bega, M Gramaglia, M Fiore… - … -IEEE conference on …, 2019 - ieeexplore.ieee.org
Network slicing is a new paradigm for future 5G networks where the network infrastructure is
divided into slices devoted to different services and customized to their needs. With this …

DeepCog: Optimizing resource provisioning in network slicing with AI-based capacity forecasting

D Bega, M Gramaglia, M Fiore… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
The dynamic management of network resources is both a critical and challenging task in
upcoming multi-tenant mobile networks, which requires allocating capacity to individual …

Health risks associated with 5G exposure: A view from the communications engineering perspective

L Chiaraviglio, A Elzanaty… - IEEE Open Journal of the …, 2021 - ieeexplore.ieee.org
The deployment of the fifth-generation (5G) wireless communication services requires the
installation of 5G next-generation Node-B Base Stations (gNBs) over the territory and the …

On the specialization of fdrl agents for scalable and distributed 6g ran slicing orchestration

F Rezazadeh, L Zanzi, F Devoti… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Network slicing enables multiple virtual networks to be instantiated and customized to meet
heterogeneous use case requirements over 5G and beyond network deployments …

TRANSIT: Fine-grained human mobility trajectory inference at scale with mobile network signaling data

L Bonnetain, A Furno, NE El Faouzi, M Fiore… - … Research Part C …, 2021 - Elsevier
Call detail records (CDR) collected by mobile phone network providers have been largely
used to model and analyze human-centric mobility. Despite their potential, they are limited in …

Applying big data, machine learning, and SDN/NFV to 5G traffic clustering, forecasting, and management

LV Le, D Sinh, BSP Lin, LP Tung - 2018 4th IEEE Conference …, 2018 - ieeexplore.ieee.org
Traffic clustering, forecasting, and management play a crucial role in improving network
efficiency, network quality, load balancing (LB), and energy saving of mobile networks …

Not all apps are created equal: Analysis of spatiotemporal heterogeneity in nationwide mobile service usage

C Marquez, M Gramaglia, M Fiore, A Banchs… - Proceedings of the 13th …, 2017 - dl.acm.org
We investigate how individual mobile services are consumed at a national scale, by
studying data collected in a 3G/4G mobile network deployed over a major European country …

Data-driven evaluation of anticipatory networking in LTE networks

N Bui, J Widmer - IEEE Transactions on Mobile Computing, 2018 - ieeexplore.ieee.org
Anticipatory networking is a recent branch of network optimization based on prediction of the
system state. Our work specifically tackles prediction-driven resource allocation for mobile …

Cache optimization models and algorithms

G Paschos, G Iosifidis, G Caire - Foundations and Trends® in …, 2020 - nowpublishers.com
Caching refers to the act of replicating information at a faster (or closer) medium with the
purpose of improving performance. This deceptively simple idea has given rise to some of …