Machine and deep learning for resource allocation in multi-access edge computing: A survey

H Djigal, J Xu, L Liu, Y Zhang - IEEE Communications Surveys …, 2022 - ieeexplore.ieee.org
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …

Deep configuration performance learning: A systematic survey and taxonomy

J Gong, T Chen - ACM Transactions on Software Engineering and …, 2024 - dl.acm.org
Performance is arguably the most crucial attribute that reflects the quality of a configurable
software system. However, given the increasing scale and complexity of modern software …

[PDF][PDF] Security enhancement by identifying attacks using machine learning for 5G network

H Keserwani, H Rastogi, AZ Kurniullah… - International Journal …, 2022 - researchgate.net
Need of security enhancement for 5G network has been increased in last decade. Data
transmitted over network need to be secure from external attacks. Thus there is need to …

[HTML][HTML] A multi-objective approach for energy-efficient and reliable dynamic VM consolidation in cloud data centers

MH Sayadnavard, AT Haghighat… - Engineering science and …, 2022 - Elsevier
The rapid growth of cloud computing in the last decade has led to an increasing concern
about the energy requirement of cloud data centers. Dynamic virtual machine (VM) …

Edge computing-enabled Internet of Vehicles: Towards federated learning empowered scheduling

F Sun, Z Zhang, S Zeadally, G Han… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Classical edge computing algorithms assume that the execution time is always known in
resource allocation. However, in practice, the execution time in the edge server is hard to …

Machine learning threatens 5G security

J Suomalainen, A Juhola, S Shahabuddin… - IEEE …, 2020 - ieeexplore.ieee.org
Machine learning (ML) is expected to solve many challenges in the fifth generation (5G) of
mobile networks. However, ML will also open the network to several serious cybersecurity …

A two-stage multi-population genetic algorithm with heuristics for workflow scheduling in heterogeneous distributed computing environments

Y **e, FX Gui, WJ Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Workflow scheduling in Heterogeneous Distributed Computing Environments (HDCEs) is a
NP-hard problem. Although a number of scheduling approaches have been proposed for …

Resource allocation and task offloading for heterogeneous real-time tasks with uncertain duration time in a fog queueing system

L Li, Q Guan, L **, M Guo - Ieee Access, 2019 - ieeexplore.ieee.org
Fog computing has become the primary infrastructure on the Internet for improving the
quality of service. We consider a fog queueing system with limited infrastructure resources to …

Reliability based workflow scheduling on cloud computing with deadline constraint

S Khurana, G Sharma, M Kumar, N Goyal… - Wireless Personal …, 2023 - Springer
Distributed computing workflow is an effective paradigm to express a range of applications
with cloud computing platforms for scientific research explorations. One of the most difficult …

Lotaru: Locally predicting workflow task runtimes for resource management on heterogeneous infrastructures

J Bader, F Lehmann, L Thamsen, U Leser… - Future Generation …, 2024 - Elsevier
Many resource management techniques for task scheduling, energy and carbon efficiency,
and cost optimization in workflows rely on a-priori task runtime knowledge. Building runtime …