A survey on scheduling techniques in computing and network convergence

S Tang, Y Yu, H Wang, G Wang, W Chen… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The computing demand for massive applications has led to the ubiquitous deployment of
computing power. This trend results in the urgent need for higher-level computing resource …

Modeling, detecting, and mitigating threats against industrial healthcare systems: a combined software defined networking and reinforcement learning approach

P Radoglou-Grammatikis, K Rompolos… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The rise of the Internet of Medical Things introduces the healthcare ecosystem in a new
digital era with multiple benefits, such as remote medical assistance, real-time monitoring …

Security challenges for workflow allocation model in cloud computing environment: a comprehensive survey, framework, taxonomy, open issues, and future directions

M Alam, M Shahid, S Mustajab - The Journal of Supercomputing, 2024 - Springer
In cloud computing environment, the workflow allocation mainly focuses on task assignment
to satisfy the quality-of-service (QoS) standards and workload balancing by the best use of …

A multiple-kernel clustering based intrusion detection scheme for 5G and IoT networks

N Hu, Z Tian, H Lu, X Du, M Guizani - International Journal of Machine …, 2021 - Springer
The 5G network provides higher bandwidth and lower latency for edge IoT devices to access
the core business network. But at the same time, it also expands the attack surface of the …

A deep reinforcement learning-based preemptive approach for cost-aware cloud job scheduling

L Cheng, Y Wang, F Cheng, C Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With some specific characteristics such as elastics and scalability, cloud computing has
become the most promising technology for online business nowadays. However, how to …

ECFA: an efficient convergent firefly algorithm for solving task scheduling problems in cloud-edge computing

L Yin, J Sun, J Zhou, Z Gu, K Li - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In cloud-edge computing paradigms, the integration of edge servers and task offloading
mechanisms has posed new challenges to develo** task scheduling strategies. This …

Emerging vm threat prediction and dynamic workload estimation for secure resource management in industrial clouds

D Saxena, R Gupta, AK Singh… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The inefficient sharing of industrial cloud resour-ces among multiple users and
vulnerabilities of virtual machines (VM) s and servers prompt unauthorized access to users' …

Q-learning and LSTM based deep active learning strategy for malware defense in industrial IoT applications

SA Khowaja, P Khuwaja - Multimedia Tools and Applications, 2021 - Springer
Edge devices are extensively used as intermediaries between the device and the service
layer in an industrial Internet of things (IIoT) environment. These devices are quite …

An enhanced bacterial foraging optimization algorithm for secure data storage and privacy-preserving in cloud

K Anand, A Vijayaraj, M Vijay Anand - Peer-to-Peer Networking and …, 2022 - Springer
Cloud file access is the most widely used peer-to-peer (P2P) application, in which users
share their data and other users can access it via P2P networks. The need for security in the …

Task scheduling in real-time industrial scenarios

G Chen, J Zhang, M Ning, W Cui, M Ma - Computers & Industrial …, 2023 - Elsevier
Task scheduling for microservice-oriented industrial software is a complex process. It is a
real-time process where multiple task attributes should be considered and different tasks …