[HTML][HTML] AI augmented Edge and Fog computing: Trends and challenges

S Tuli, F Mirhakimi, S Pallewatta, S Zawad… - Journal of Network and …, 2023 - Elsevier
In recent years, the landscape of computing paradigms has witnessed a gradual yet
remarkable shift from monolithic computing to distributed and decentralized paradigms such …

Multi-search-routes-based methods for minimizing makespan of homogeneous and heterogeneous resources in Cloud computing

G Zhou, W Tian, R Buyya - Future Generation Computer Systems, 2023 - Elsevier
Cloud computing, as a large-scale distributed computing system dynamically providing
elastic services, is designed to meet the requirement of delivering computing services to …

NTAM: neighborhood-temporal attention model for disk failure prediction in cloud platforms

C Luo, P Zhao, B Qiao, Y Wu, H Zhang, W Wu… - Proceedings of the Web …, 2021 - dl.acm.org
With the rapid deployment of cloud platforms, high service reliability is of critical importance.
An industrial cloud platform contains a huge number of disks, and disk failure is a common …

Beyond pairwise testing: Advancing 3-wise combinatorial interaction testing for highly configurable systems

C Luo, S Lyu, Q Zhao, W Wu, H Zhang… - Proceedings of the 33rd …, 2024 - dl.acm.org
To meet the rising demand for software customization, highly configurable software systems
play key roles in practice. Combinatorial interaction testing (CIT) is recognized as an …

Solving the t-Wise Coverage Maximum Problem via Effective and Efficient Local Search-Based Sampling

C Luo, J Song, Q Zhao, B Sun, J Chen… - ACM Transactions on …, 2024 - dl.acm.org
To meet the increasing demand for customized software, highly configurable systems
become essential in practice. Such systems offer many options to configure, and ensuring …

Performance and cost-aware task scheduling via deep reinforcement learning in cloud environment

Z Zhao, X Shi, M Shang - International Conference on Service-Oriented …, 2022 - Springer
In the cloud computing environment, task scheduling with multiple objectives optimization
becomes a highly challenging problem in such a dynamic and bursty environment. Previous …

Edits: An easy-to-difficult training strategy for cloud failure prediction

Q Lin, T Li, P Zhao, Y Liu, M Ma, L Zheng… - … Proceedings of the …, 2023 - dl.acm.org
Cloud failures have been a major threat to the reliability of cloud services. Many failure
prediction approaches have been proposed to predict cloud failures before they actually …

CAmpactor: A novel and effective local search algorithm for optimizing pairwise covering arrays

Q Zhao, C Luo, S Cai, W Wu, J Lin, H Zhang… - Proceedings of the 31st …, 2023 - dl.acm.org
The increasing demand for software customization has led to the development of highly
configurable systems. Combinatorial interaction testing (CIT) is an effective method for …

SamplingCA: effective and efficient sampling-based pairwise testing for highly configurable software systems

C Luo, Q Zhao, S Cai, H Zhang, C Hu - … of the 30th ACM Joint European …, 2022 - dl.acm.org
Combinatorial interaction testing (CIT) is an effective paradigm for testing highly
configurable systems, and its goal is to generate a t-wise covering array (CA) as a test suite …

CILP: Co-simulation-based imitation learner for dynamic resource provisioning in cloud computing environments

S Tuli, G Casale, NR Jennings - IEEE Transactions on Network …, 2023 - ieeexplore.ieee.org
Intelligent Virtual Machine (VM) provisioning is central to cost and resource efficient
computation in cloud computing environments. As bootstrap** VMs is time-consuming, a …