EconPapers    
Economics at your fingertips  
 

Load-balancing scheduling of simulation tasks based on a static-dynamic hybrid algorithm

Xiashuang Wang, Ni Li, Guanghong Gong, Xiao Song and Yanqi Guo

Journal of Simulation, 2022, vol. 16, issue 2, 182-193

Abstract: A scheduling algorithm is crucial for running a simulation model so that tasks can be performed efficiently.The traditionally used blade-based parallel engine system cannot be adapted to a new simulation model. This study proposed a combined dynamic priority and static method, that is, a hybrid load-balancing scheduling (HLB) algorithm. The algorithm is given priority according to the operating cycle of the model and system steps. The experimental results demonstrated that the algorithm outperformed the earliest deadline first and the time-stepped load-balancing scheduling algorithms. The results also demonstrated that the HLBhad a higher real-time operating efficiency than the other algorithms under a lower overhead guarantee. The HLB algorithm causedbetter performance while maintaining computation and communication efficiency. Simultaneously, the utilisation rate of the central processing unit was around 35%.The further study should be enhanced to generalise it so that it could be applied to incorporate load balancing.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/17477778.2020.1772023 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjsmxx:v:16:y:2022:i:2:p:182-193

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjsm20

DOI: 10.1080/17477778.2020.1772023

Access Statistics for this article

Journal of Simulation is currently edited by Christine Currie

More articles in Journal of Simulation from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tjsmxx:v:16:y:2022:i:2:p:182-193