A survey on mobile edge computing for video streaming: Opportunities and challenges
5G communication brings substantial improvements in the quality of service provided to
various applications by achieving higher throughput and lower latency. However, interactive …
various applications by achieving higher throughput and lower latency. However, interactive …
Machine learning for industry 4.0: a systematic review using deep learning-based topic modelling
D Mazzei, R Ramjattan - Sensors, 2022 - mdpi.com
Machine learning (ML) has a well-established reputation for successfully enabling
automation through its scalable predictive power. Industry 4.0 encapsulates a new stage of …
automation through its scalable predictive power. Industry 4.0 encapsulates a new stage of …
Joint task offloading and resource allocation for energy-constrained mobile edge computing
We consider the problem of task offloading and resource allocation in mobile edge
computing (MEC). To maintain satisfactory quality of experience (QoE) of end-users, mobile …
computing (MEC). To maintain satisfactory quality of experience (QoE) of end-users, mobile …
Learning combinatorial optimization on graphs: A survey with applications to networking
Existing approaches to solving combinatorial optimization problems on graphs suffer from
the need to engineer each problem algorithmically, with practical problems recurring in …
the need to engineer each problem algorithmically, with practical problems recurring in …
Deep learning for edge computing applications: A state-of-the-art survey
With the booming development of Internet-of-Things (IoT) and communication technologies
such as 5G, our future world is envisioned as an interconnected entity where billions of …
such as 5G, our future world is envisioned as an interconnected entity where billions of …
Threats of adversarial attacks in DNN-based modulation recognition
With the emergence of the information age, mobile data has become more random,
heterogeneous and massive. Thanks to its many advantages, deep learning is increasingly …
heterogeneous and massive. Thanks to its many advantages, deep learning is increasingly …
Intelligent video caching at network edge: A multi-agent deep reinforcement learning approach
Today's explosively growing Internet video traffics and viewers' ever-increasing quality of
experience (QoE) demands for video streaming bring tremendous pressures to the …
experience (QoE) demands for video streaming bring tremendous pressures to the …
Load-balanced virtual network embedding based on deep reinforcement learning for 6G regional satellite networks
Regional satellite networks are capable of supporting denser coverage and more reliable
communications in the target area and hence have been viewed as an essential part of the …
communications in the target area and hence have been viewed as an essential part of the …
Towards crowdsourcing internet of things (crowd-iot): Architectures, security and applications
KLM Ang, JKP Seng, E Ngharamike - Future Internet, 2022 - mdpi.com
Crowdsourcing can play an important role in the Internet of Things (IoT) applications for
information sensing and gathering where the participants are equipped with geolocated …
information sensing and gathering where the participants are equipped with geolocated …
Dependency-aware application assigning and scheduling in edge computing
Mobile-edge computing (MEC) is booming in recent years, as it is expected to fulfill the
growing low-latency requirements of offloaded applications on large amounts of end …
growing low-latency requirements of offloaded applications on large amounts of end …