Research on strong agile response task scheduling optimization enhancement with optimal resource usage in green cloud computing

Virtualization technology provides a new way to improve resource utilization and cloud service throughput. However, the randomness of task arrival, tight coupling between resource load imbalance and node heterogeneity, high computing power, and other factors have hindered the energy consumption opti...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Future generation computer systems Ročník 124; s. 12 - 20
Hlavní autoři: Shu, Wanneng, Cai, Ken, Xiong, Neal Naixue
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.11.2021
Témata:
Agile response
Cloud server resource pool
Green cloud computing
Task scheduling
Virtualization technology
Task scheduling
Agile response
Cloud server resource pool
Virtualization technology
Green cloud computing
ISSN:0167-739X, 1872-7115
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Virtualization technology provides a new way to improve resource utilization and cloud service throughput. However, the randomness of task arrival, tight coupling between resource load imbalance and node heterogeneity, high computing power, and other factors have hindered the energy consumption optimization and cost reduction objectives of the existing technology. Consequently, task scheduling failure cannot be easily eliminated, and cloud computing performance is decreased dramatically. In this study, a strong agile response task scheduling optimization algorithm is proposed on the basis of the peak energy consumption of data centers and the time span of task scheduling. Agile response optimization techniques are also adopted. From the perspective of task failure rate, the proposed algorithm can be used to investigate the strong agile response optimization model, explore the probability density function of the task request queue overflow, and request a timeout to avoid network congestion. Experimental results indicate that the proposed algorithm can achieve the stability and efficiency of task scheduling and effectively improve the throughput of the cloud computing system. •An effective agile response optimization model.•A novel task scheduling optimization model.•A strong agile response task scheduling optimization algorithm.
ISSN:0167-739X
1872-7115
DOI:10.1016/j.future.2021.05.012