Resource Provisioning Based Scheduling Framework for Execution of Heterogeneous and Clustered Workloads in Clouds: from Fundamental to Autonomic Offering-Reference-Cited by-同舟云学术

Resource Provisioning Based Scheduling Framework for Execution of Heterogeneous and Clustered Workloads in Clouds: from Fundamental to Autonomic Offering

Published:2018-01-19 Issue:3 Volume:17 Page:385-417
ISSN:1570-7873
Container-title:Journal of Grid Computing
language:en
Short-container-title:J Grid Computing

Author:

Gill Sukhpal Singh^ORCID,Buyya Rajkumar

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Information Systems,Software

Link

http://link.springer.com/article/10.1007/s10723-017-9424-0/fulltext.html

Reference50 articles.

1. Varghese, B., Buyya, R.: Next generation cloud computing: New trends and research directions. Future Generation Comput. Syst. 79, 849–861 (2017). https://doi.org/10.1016/j.future.2017.09.020

2. Qi, Z.T.L., Cheng, Z., Li, K., Khan, S.U., Li, K.: An energy-efficient task scheduling algorithm in DVFS-enabled cloud environment. J. Grid Comput. 14(1), 55–74 (2016)

3. de Carvalho, O.A. Jr, Adilson, O., Bruschi, S.M., Santana, R.H.C., Santana, M.J.: Green cloud meta-scheduling. J. Grid Comput. 14(1), 109–126 (2016)

4. Jiang, J., Lin, Y., Xie, G., Fu, L., Yang, J.: Time and Energy Optimization Algorithms for the Static Scheduling of Multiple Workflows in Heterogeneous Computing System. J. Grid Comput., 1–22 (2017). https://doi.org/10.1007/s10723-017-9391-5

5. Ebrahimirad, V., Goudarzi, M., Rajabi, A.: Energy-aware scheduling for precedence-constrained parallel virtual machines in virtualized data centers. J. Grid Comput. 13(2), 233–253 (2015)

Cited by 59 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. CSO-based Efficient Resource Management for Sustainable Cloud Computing;Contemporary Mathematics;2024-03-29

2. Artificial Intelligence Powered Autonomic Computing and its Applications;SSRN Electronic Journal;2024

3. Enhancement of Cloud-native applications with Autonomic Features;Journal of Grid Computing;2023-07-15

4. A Brief Survey of Energy-Efficient Task Scheduling Algorithms in the Cloud;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06

5. A Study on Self-Configuring Intrusion Detection Model based on Hybridized Deep Learning Models;2023 7th International Conference on Computing Methodologies and Communication (ICCMC);2023-02-23