Ai-based mobile edge computing for iot: Applications, challenges, and future scope
New technology is needed to meet the latency and bandwidth issues present in cloud
computing architecture specially to support the currency of 5G networks. Accordingly, mobile …
computing architecture specially to support the currency of 5G networks. Accordingly, mobile …
Federaser: Enabling efficient client-level data removal from federated learning models
Federated learning (FL) has recently emerged as a promising distributed machine learning
(ML) paradigm. Practical needs of the" right to be forgotten" and countering data poisoning …
(ML) paradigm. Practical needs of the" right to be forgotten" and countering data poisoning …
Applications and challenges of federated learning paradigm in the big data era with special emphasis on COVID-19
A Majeed, X Zhang, SO Hwang - Big Data and Cognitive Computing, 2022 - mdpi.com
Federated learning (FL) is one of the leading paradigms of modern times with higher privacy
guarantees than any other digital solution. Since its inception in 2016, FL has been …
guarantees than any other digital solution. Since its inception in 2016, FL has been …
[HTML][HTML] Evolutionary privacy-preserving learning strategies for edge-based IoT data sharing schemes
The fast proliferation of edge devices for the Internet of Things (IoT) has led to massive
volumes of data explosion. The generated data is collected and shared using edge-based …
volumes of data explosion. The generated data is collected and shared using edge-based …
Exploring the landscape of learning analytics privacy in fog and edge computing: A systematic literature review
The study systematically reviews the integration of Fog and Edge Computing within
Learning Analytics to enhance data privacy and security in educational settings that use …
Learning Analytics to enhance data privacy and security in educational settings that use …
Efficient rate-splitting multiple access for the Internet of Vehicles: Federated edge learning and latency minimization
Rate-Splitting Multiple Access (RSMA) has recently found favour in the multi-antenna-aided
wireless downlink, as a benefit of relaxing the accuracy of Channel State Information at the …
wireless downlink, as a benefit of relaxing the accuracy of Channel State Information at the …
Unsupervised recurrent federated learning for edge popularity prediction in privacy-preserving mobile-edge computing networks
Nowadays, wireless communication is rapidly reshaping entire industry sectors. In particular,
mobile-edge computing (MEC) as an enabling technology for the Industrial Internet of …
mobile-edge computing (MEC) as an enabling technology for the Industrial Internet of …
[HTML][HTML] An approach for proactive mobile recommendations based on user-defined rules
S Ilarri, R Trillo-Lado - Expert Systems with Applications, 2024 - Elsevier
Abstract In the Big Data era, context-aware mobile recommender systems are crucial in
assisting citizens and tourists in making informed decisions, providing a suitable way for …
assisting citizens and tourists in making informed decisions, providing a suitable way for …
Partially-federated learning: A new approach to achieving privacy and effectiveness
M Fisichella, G Lax, A Russo - Information Sciences, 2022 - Elsevier
Abstract In Machine Learning, the data for training the model are stored centrally. However,
when the data come from different sources and contain sensitive information, we can use …
when the data come from different sources and contain sensitive information, we can use …
A comprehensive analysis of privacy protection techniques developed for COVID-19 pandemic
A Majeed, SO Hwang - IEEE Access, 2021 - ieeexplore.ieee.org
Since the emergence of coronavirus disease–2019 (COVID-19) outbreak, every country has
implemented digital solutions in the form of mobile applications, web-based frameworks …
implemented digital solutions in the form of mobile applications, web-based frameworks …