Cited by A novel virtual machine consolidation algorithm with server power mode management for energy-efficient cloud data centers

Machine learning (ML)-centric resource management in cloud computing: A review and future directions DOI

Tahseen Khan, Wenhong Tian, Guangyao Zhou

et al.

Journal of Network and Computer Applications, Journal Year: 2022, Volume and Issue: 204, P. 103405 - 103405

Published: May 6, 2022

Language: Английский

Citations

Future data center energy-conservation and emission-reduction technologies in the context of smart and low-carbon city construction DOI

Hongyu Zhu,

Dongdong Zhang,

Hui Hwang Goh

et al.

Sustainable Cities and Society, Journal Year: 2022, Volume and Issue: 89, P. 104322 - 104322

Published: Nov. 25, 2022

Language: Английский

Citations

REVIEW OF EVOLVING CLOUD COMPUTING PARADIGMS: SECURITY, EFFICIENCY, AND INNOVATIONS DOI

Ogugua Chimezie,

Samuel Onimisi Dawodu,

Andrew Ifesinachi Daraojimba

et al.

Computer Science & IT Research Journal, Journal Year: 2024, Volume and Issue: 5(2), P. 270 - 292

Published: Feb. 2, 2024

The paper provides a comprehensive analysis of the dynamic landscape cloud computing, with focus on security, efficiency, and innovative trends. It delves into evolving paradigms that shape current state offering insights challenges opportunities arise as technology continues to advance. Security is central theme in review, addressing critical concerns associated data privacy, integrity, access control environments. study explores latest security measures protocols implemented safeguard sensitive information, emphasizing importance robust frameworks an era marked by cyber threats vulnerabilities. Efficiency another key aspect under scrutiny, review evaluating performance optimization strategies, resource allocation mechanisms, scalability solutions. authors examine how providers are adapting meet growing demand for efficient sustainable computing resources, highlighting best practices emerging trends contribute enhanced performance. Furthermore, sheds light shaping future computing. cutting-edge technologies, such edge serverless architectures, containerization, their impact reshaping landscape. concludes summarizing takeaways understanding ensure secure, efficient, digital future. Keywords: Cloud Computing, Information Technology, Security, Innovations, Review.

Language: Английский

Citations

Multi-objective fuzzy approach to scheduling and offloading workflow tasks in Fog–Cloud computing DOI

Marwa Mokni, Sonia Yassa,

Jalel Eddine Hajlaoui

et al.

Simulation Modelling Practice and Theory, Journal Year: 2022, Volume and Issue: 123, P. 102687 - 102687

Published: Nov. 8, 2022

Language: Английский

Citations

A systematic review of green-aware management techniques for sustainable data center DOI

Weiwei Lin, Jianpeng Lin, Zhiping Peng

et al.

Sustainable Computing Informatics and Systems, Journal Year: 2024, Volume and Issue: 42, P. 100989 - 100989

Published: April 1, 2024

Language: Английский

Citations

Containerization in Multi-Cloud Environment: Roles, Strategies, Challenges, and Solutions for Effective Implementation DOI

Muhammad Waseem, Aakash Ahmad, Peng Liang

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

Multivariate workload and resource prediction in cloud computing using CNN and GRU by attention mechanism DOI

Javad Dogani, Farshad Khunjush,

Mohammad Reza Mahmoudi

et al.

The Journal of Supercomputing, Journal Year: 2022, Volume and Issue: 79(3), P. 3437 - 3470

Published: Sept. 4, 2022

Language: Английский

Citations

Proficient job scheduling in cloud computation using an optimized machine learning strategy DOI

P. Neelakantan, N. Sudhakar Yadav

International Journal of Information Technology, Journal Year: 2023, Volume and Issue: 15(5), P. 2409 - 2421

Published: May 12, 2023

Language: Английский

Citations

Cooperative agents-based approach for workflow scheduling on fog-cloud computing DOI

Marwa Mokni, Sonia Yassa,

Jalel Eddine Hajlaoui

et al.

Journal of Ambient Intelligence and Humanized Computing, Journal Year: 2021, Volume and Issue: 13(10), P. 4719 - 4738

Published: April 1, 2021

Language: Английский

Citations

Low-power multi-cloud deployment of large distributed service applications with response-time constraints DOI

Babneet Singh,

Ravneet Kaur, Murray Woodside

et al.

Journal of Cloud Computing Advances Systems and Applications, Journal Year: 2023, Volume and Issue: 12(1)

Published: Jan. 3, 2023

Abstract Distributed service applications make heavy use of clouds and multi-clouds, must (i) meet quality goals (e.g. response time) while (ii) satisfying cloud resource constraints (iii) conserving power. Deployment algorithms (iv) provide a solution meeting these requirements within short time to be useful in practice. Very few existing deployment methods address the first three requirements, those that do take too long find deployment. The Low-Power Multi-Cloud Application (LPD) algorithm fills this gap with low-complexity heuristic combination generalized graph partitioning between clouds, bin-packing each queueing approximations control time. LPD has no known competitor quickly finds satisfies bounds. A host execution approximation for contention is fundamental achieving sufficient speed. intended by managers who simultaneously manage hosts application deployments plan capacity offer services such as Serverless Computing. On 104 test scenarios deploying up 200 processes 240 replicas (for scaling), always produced feasible 100 s (within 20 seconds over three-quarters cases). Compared Mixed Integer Program CPLEX (which took lot longer was sometimes not found) solutions gave power consumption equal MIP third cases 6% 95% cases. In 93% all 20% an (unachievable) lower bound. stand-alone restrictions, but could easily adapted repair mechanism Genetic Algorithm.

Language: Английский

Citations