Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Apostolos Galanopoulos"'
Autor:
Andy Donald, Apostolos Galanopoulos, Edward Curry, Emir Munoz, Ihsan Ullah, M. A. Waskow, Maciej Dabrowski, Manan Kalra
Publikováno v:
IEEE Access, Vol 11, Pp 53703-53715 (2023)
With the increase in usage of machine learning models within many different aspects of customer interactions, it has become very clear that bias detection within associated customer interaction datasets has led to a critical focus on issues such as t
Externí odkaz:
https://doaj.org/article/140b5c56bca04e7e9e3604fa879262bb
Publikováno v:
IEEE Transactions on Network and Service Management. 19:3090-3104
—An increasing number of mobile applications rely on Machine Learning (ML) routines for analyzing data. Executing such tasks at the user devices saves the energy spent on transmitting and processing large data volumes at distant cloud-deployed serv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3af2d5b4e7774bbcaf27e68bed446186
https://doi.org/10.1109/tnsm.2022.3174776
https://doi.org/10.1109/tnsm.2022.3174776
Autor:
Andy Donald, Apostolos Galanopoulos, Edward Curry, Emir Muñoz, Ihsan Ullah, M. A. Waskow, Maciej Dabrowski, Manan Kalra
Publikováno v:
Companion Proceedings of the ACM Web Conference 2023.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3eda28dd843071697de906b9882c28b3
https://doi.org/10.1145/3543873.3587659
https://doi.org/10.1145/3543873.3587659
Publikováno v:
IEEE Transactions on Cognitive Communications and Networking. 6:1166-1179
Internet of Things (IoT) networks are increasingly used for edge data analytics, i.e., collecting and analyzing data at the network edge. However, the IoT devices are typically resource-constrained and cannot support fast and accurate execution of su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::169e46526dfdef117ee2e5d2995b9ac8
https://doi.org/10.1109/tccn.2020.3019610
https://doi.org/10.1109/tccn.2020.3019610
Publikováno v:
IEEE Transactions on Signal and Information Processing over Networks. 6:382-393
In this paper, we consider a heterogeneous network consisting of both macro Base Station (MBS) and pico Base Stations (PBSs) in order to provide a spectrum allocation and mode selection in device-to-device (D2D) communications. A number of Component
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fccb666a3a875b62d96bda5dab2a3d08
https://doi.org/10.1109/tsipn.2020.2994008
https://doi.org/10.1109/tsipn.2020.2994008
Publikováno v:
Wireless Personal Communications. 111:1545-1562
Next generation wireless networks are becoming the main focus of the industry by putting efforts to launch beyond 4G (i.e. 5G) communication systems by 2020. Towards the 5G-system vision, the efficient spectrum aggregation by integrating multiple rad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::502448df2edc9882e3b3d4d9dcde170b
https://doi.org/10.1007/s11277-019-06939-1
https://doi.org/10.1007/s11277-019-06939-1
Publikováno v:
INFOCOM 2021-IEEE Conference on Computer Communications
INFOCOM
INFOCOM
Video analytics constitute a core component of many wireless services that require processing of voluminous data streams emanating from handheld devices. Multi-Access Edge Computing (MEC) is a promising solution for supporting such resource-hungry se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f0c6d160e904d0330f61d7f9a54a67c2
Publikováno v:
GLOBECOM
Real-time object recognition is becoming an essen-tial part of many emerging services, such as augmented reality, which require accurate inference in a timely fashion with low delay. We consider an edge-assisted object recognition system that can be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de832a08fe3328c2677cc29dd20d4d64
https://doi.org/10.1109/globecom42002.2020.9322146
https://doi.org/10.1109/globecom42002.2020.9322146
Publikováno v:
ICTC
In this paper, we explore an impact of GPU/CPU scaling of a state-of-the-art AI embedded device on its energy consumption and AI performance. We use Nvidia Jetson TX2 as an experiment device thanks to its tractability to scale GPU/CPU and modify AI f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf15d2e95e62ac13ab00e50f8e4eaca9
https://doi.org/10.1109/ictc49870.2020.9289270
https://doi.org/10.1109/ictc49870.2020.9289270
Autor:
Argyrios G. Tasiopoulos, Theodoros Salonidis, George Iosifidis, Douglas J. Leith, Apostolos Galanopoulos
Publikováno v:
ICC
A large number of emerging IoT applications rely on machine learning routines for analyzing data. Executing such tasks at the user devices improves response time and economizes network resources. However, due to power and computing limitations, the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2aa0e470ae01393ca32cf37419222e1
http://arxiv.org/abs/2003.03588
http://arxiv.org/abs/2003.03588