Cluster resource scheduling in cloud computing: literature review and research challenges

W Khallouli, J Huang - The Journal of supercomputing, 2022 - Springer
Scheduling plays a pivotal role in cloud computing systems. Designing an efficient
scheduler is a challenging task. The challenge comes from several aspects, including the …

Federated against the cold: A trust-based federated learning approach to counter the cold start problem in recommendation systems

OA Wahab, G Rjoub, J Bentahar, R Cohen - Information Sciences, 2022 - Elsevier
Recommendation systems are often challenged by the existence of cold-start items for which
no previous rating is available. The standard content-based or collaborative-filtering …

Enhanced multi-verse optimizer for task scheduling in cloud computing environments

SE Shukri, R Al-Sayyed, A Hudaib, S Mirjalili - Expert Systems with …, 2021 - Elsevier
Cloud computing is a trending technology that allows users to use computing resources
remotely in a pay-per-use model. One of the main challenges in cloud computing …

Deep reinforcement learning-based methods for resource scheduling in cloud computing: A review and future directions

G Zhou, W Tian, R Buyya, R Xue, L Song - Artificial Intelligence Review, 2024 - Springer
With the acceleration of the Internet in Web 2.0, Cloud computing is a new paradigm to offer
dynamic, reliable and elastic computing services. Efficient scheduling of resources or …

Discovering the role of trade diversification, natural resources, and environmental policy stringency on ecological sustainability in the BRICST region

S Dai, X Du - Resources Policy, 2023 - Elsevier
Understanding the role of trade diversification, natural resources, and environmental
policies is crucial for achieving ecological sustainability. By unraveling the interactions …

Deep and reinforcement learning for automated task scheduling in large‐scale cloud computing systems

G Rjoub, J Bentahar, O Abdel Wahab… - Concurrency and …, 2021 - Wiley Online Library
Cloud computing is undeniably becoming the main computing and storage platform for
today's major workloads. From Internet of things and Industry 4.0 workloads to big data …

FUPE: A security driven task scheduling approach for SDN-based IoT–Fog networks

S Javanmardi, M Shojafar, R Mohammadi… - Journal of information …, 2021 - Elsevier
Fog computing is a paradigm to overcome the cloud computing limitations which provides
low latency to the users' applications for the Internet of Things (IoT). Software-defined …

[HTML][HTML] Multi-objective task scheduling optimization in cloud computing based on fuzzy self-defense algorithm

X Guo - Alexandria Engineering Journal, 2021 - Elsevier
A cloud computing multi-objective task scheduling optimization based on fuzzy self-defense
algorithm is proposed. Select the shortest time, the degree of resource load balance and the …

A survey on explainable artificial intelligence for cybersecurity

G Rjoub, J Bentahar, OA Wahab… - … on Network and …, 2023 - ieeexplore.ieee.org
The “black-box” nature of artificial intelligence (AI) models has been the source of many
concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a …

Trust-driven reinforcement selection strategy for federated learning on IoT devices

G Rjoub, OA Wahab, J Bentahar, A Bataineh - Computing, 2024 - Springer
Federated learning is a distributed machine learning approach that enables a large number
of edge/end devices to perform on-device training for a single machine learning model …