Integration of an Event-Based Simulation Framework into a Scientific Workflow Execution Environment for Grids and Clouds

2011 ◽  
pp. 1-13 ◽  
Author(s):  
Simon Ostermann ◽  
Kassian Plankensteiner ◽  
Daniel Bodner ◽  
Georg Kraler ◽  
Radu Prodan
Keyword(s):  
Scientific Workflow ◽  
Simulation Framework ◽  
Workflow Execution ◽  
Execution Environment ◽  
Event Based

Simulation of Wind Farm Operations and Maintenance

2013 ◽  
Author(s):  
Eduardo Pérez ◽  
Lewis Ntaimo ◽  
Yu Ding
Keyword(s):  
Wind Farm ◽  
Discrete Event ◽  
Maintenance Scheduling ◽  
Simulation Framework ◽  
Structural Element ◽  
Maintenance Strategies ◽  
Random Events ◽  
Operations And Maintenance ◽  
Event Based ◽  
Commercial Size

We develop a discrete event-based simulation framework that mimics the operations of a commercial size wind farm. Each turbine is treated as separate module, so that the simulation can be easily scaled up to more than one hundred turbines for a farm. Each turbine module includes a structural element sub-module, degradation sub-module, power generation sub-module, sensing and maintenance scheduling sub-module. The simulator is specially designed to handle a large number of unorganized random events (turbine failures, waiting for parts, weather disruptions) and reflect in the simulator’s outputs the variation from parameters and operations. We report on implementation results and provide insights into wind farm operations under different maintenance strategies.

A QoS-aware exception handling method in scientific workflow execution

2011 ◽  
Vol 23 (16) ◽  
pp. 1951-1968 ◽  
Author(s):  
Lianyong Qi ◽  
Wenmin Lin ◽  
Wanchun Dou ◽  
Jian Jiang ◽  
Jinjun Chen
Keyword(s):  
Exception Handling ◽  
Scientific Workflow ◽  
Workflow Execution ◽  
Handling Method

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.

Sign in / Sign up

Export Citation Format

Share Document