Cost-effective Heuristics for Workflow Scheduling in Grid Computing Economy

2007 ◽  
Author(s):  
Yingchun Yuan ◽  
Xiansong Li ◽  
Chenxia Sun
Keyword(s):  
Grid Computing ◽  
Cost Effective ◽  
Workflow Scheduling

Cost Effective Heuristic workflow scheduling algorithm in Cloud under Deadline Constraint

2019 ◽  
Vol 12 ◽  
Author(s):  
Jasraj Meena ◽  
Manu Vardhan
Keyword(s):  
Cloud Computing ◽  
Scheduling Algorithm ◽  
Cost Effective ◽  
Scientific Workflow ◽  
Scientific Workflows ◽  
Workflow Scheduling ◽  
Performance Variation ◽  
Acquisition Delay ◽  
Very High ◽  
Deadline Constraint

Cloud computing is used to deliver IT resources over the internet. Due to the popularity of cloud computing, nowadays, most of the scientific workflows are shifted towards this environment. There are lots of algorithms has been proposed in the literature to schedule scientific workflows in the cloud, but their execution cost is very high as well as they are not meeting the user-defined deadline constraint. This paper focuses on satisfying the userdefined deadline of a scientific workflow while minimizing the total execution cost. So, to achieve this, we have proposed a Cost-Effective under Deadline (CEuD) constraint workflow scheduling algorithm. The proposed CEuD algorithm considers all the essential features of Cloud and resolves the major issues such as performance variation, and acquisition delay. We have compared the proposed CEuD algorithm with the existing literature algorithms for scientific workflows (i.e., Montage, Epigenomics, and CyberShake) and getting better results for minimizing the overall execution cost of the workflow while satisfying the user-defined deadline.

AI-Based Enhanced Time Cost-Effective Cloud Workflow Scheduling

2022 ◽  
pp. 277-297
Author(s):  
V. Lakshmi Narasimhan ◽  
V. S. Jithin ◽  
M. Ananya ◽  
Jonathan Oluranti
Keyword(s):  
Cost Effective ◽  
Workflow Scheduling ◽  
Time Cost

scholarly journals Fluctuation-Aware and Predictive Workflow Scheduling in Cost-Effective Infrastructure-as-a-Service Clouds

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 61488-61502 ◽  
Author(s):  
Weiling Li ◽  
Yunni Xia ◽  
Mengchu Zhou ◽  
Xiaoning Sun ◽  
Qingsheng Zhu
Keyword(s):  
Cost Effective ◽  
Workflow Scheduling ◽  
Infrastructure As A Service

scholarly journals Dynamic Fault-Tolerant Workflow Scheduling with Hybrid Spatial-Temporal Re-Execution in Clouds

Information ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 169 ◽  
Author(s):  
Na Wu ◽  
Decheng Zuo ◽  
Zhan Zhang
Keyword(s):  
Large Scale ◽  
Fault Tolerant ◽  
Critical Path ◽  
High Reliability ◽  
Low Cost ◽  
Cost Effective ◽  
Scientific Workflow ◽  
Workflow Scheduling ◽  
Workflow Execution ◽  
Computing Environments

Improving reliability is one of the major concerns of scientific workflow scheduling in clouds. The ever-growing computational complexity and data size of workflows present challenges to fault-tolerant workflow scheduling. Therefore, it is essential to design a cost-effective fault-tolerant scheduling approach for large-scale workflows. In this paper, we propose a dynamic fault-tolerant workflow scheduling (DFTWS) approach with hybrid spatial and temporal re-execution schemes. First, DFTWS calculates the time attributes of tasks and identifies the critical path of workflow in advance. Then, DFTWS assigns appropriate virtual machine (VM) for each task according to the task urgency and budget quota in the phase of initial resource allocation. Finally, DFTWS performs online scheduling, which makes real-time fault-tolerant decisions based on failure type and task criticality throughout workflow execution. The proposed algorithm is evaluated on real-world workflows. Furthermore, the factors that affect the performance of DFTWS are analyzed. The experimental results demonstrate that DFTWS achieves a trade-off between high reliability and low cost objectives in cloud computing environments.

scholarly journals Experiences with distributed computing for meteorological applications: Grid computing and Cloud computing

2015 ◽  
Vol 8 (2) ◽  
pp. 1171-1199 ◽  
Author(s):  
F. Schüller ◽  
S. Ostermann ◽  
R. Prodan ◽  
G. J. Mayr
Keyword(s):  
Distributed Computing ◽  
Grid Computing ◽  
High Performance ◽  
Cost Effective ◽  
Use Case ◽  
The Core ◽  
Wide Range ◽  
Different Characteristics ◽  
Performance Computing ◽  
Computing Capacity

Abstract. Experiences with three practical meteorological applications with different characteristics are used to highlight the core computer science aspects and applicability of distributed computing to meteorology. Presenting Cloud and Grid computing this paper shows use case scenarios fitting a wide range of meteorological applications from operational to research studies. The paper concludes that distributed computing complements and extends existing high performance computing concepts and allows for simple, powerful and cost effective access to computing capacity.

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