A survey of anticipatory mobile networking: Context-based classification, prediction methodologies, and optimization techniques

N Bui, M Cesana, SA Hosseini, Q Liao… - … Surveys & Tutorials, 2017 - ieeexplore.ieee.org
A growing trend for information technology is to not just react to changes, but anticipate them
as much as possible. This paradigm made modern solutions, such as recommendation …

Breadcrumbs: forecasting mobile connectivity

AJ Nicholson, BD Noble - Proceedings of the 14th ACM international …, 2008 - dl.acm.org
Mobile devices cannot rely on a single managed network, but must exploit a wide variety of
connectivity options as they travel. We argue that such systems must consider the derivative …

A survey on traffic prediction techniques using artificial intelligence for communication networks

A Chen, J Law, M Aibin - Telecom, 2021 - mdpi.com
Much research effort has been conducted to introduce intelligence into communication
networks in order to enhance network performance. Communication networks, both wired …

Context-and social-aware middleware for opportunistic networks

C Boldrini, M Conti, F Delmastro… - Journal of Network and …, 2010 - Elsevier
Opportunistic networks are multi-hop ad hoc networks in which nodes opportunistically
exploit any pair-wise contact to share and forward content, without requiring any pre-existing …

Anticipatory mobile computing: A survey of the state of the art and research challenges

V Pejovic, M Musolesi - ACM Computing Surveys (CSUR), 2015 - dl.acm.org
Today's mobile phones are far from the mere communication devices they were 10 years
ago. Equipped with sophisticated sensors and advanced computing hardware, phones can …

A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

R Boutaba, MA Salahuddin, N Limam, S Ayoubi… - Journal of Internet …, 2018 - Springer
Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …

GCN-GAN: A non-linear temporal link prediction model for weighted dynamic networks

K Lei, M Qin, B Bai, G Zhang… - IEEE INFOCOM 2019 …, 2019 - ieeexplore.ieee.org
In this paper, we generally formulate the dynamics prediction problem of various network
systems (eg, the prediction of mobility, traffic and topology) as the temporal link prediction …

A survey of online data-driven proactive 5G network optimisation using machine learning

B Ma, W Guo, J Zhang - IEEE access, 2020 - ieeexplore.ieee.org
In the fifth-generation (5G) mobile networks, proactive network optimisation plays an
important role in meeting the exponential traffic growth, more stringent service requirements …

Human mobility models for opportunistic networks

D Karamshuk, C Boldrini, M Conti… - IEEE Communications …, 2011 - ieeexplore.ieee.org
Mobile ad hoc networks enable communications between clouds of mobile devices without
the need for a preexisting infrastructure. One of their most interesting evolutions are …

Machine learning for cognitive network management

S Ayoubi, N Limam, MA Salahuddin… - IEEE …, 2018 - ieeexplore.ieee.org
Over the last decade, a significant amount of effort has been invested on architecting agile
and adaptive management solutions in support of autonomic, self-managing networks …