Optimized Task Scheduling Algorithm for Cloud Computing

Monika, .; Jindal, Abhimanyu

doi:10.1007/978-981-10-3932-4_45

Cited by 3 publications

(1 citation statement)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This algorithm determined all tasks and arranged it about large and small, the small tasks will be executed, firstly while the large task delays for a long time. The drawback of this algorithm is to assign the smaller processes to the resources with comparatively higher computational power [24].…”

Section: Min-min Algorithmmentioning

confidence: 99%

A hybrid approach for scheduling applications in cloud computing environment

Abdalkafor¹,

Alheeti²

2020

IJECE

View full text Add to dashboard Cite

Cloud computing plays an important role in our daily life. It has direct and positive impact on share and update data, knowledge, storage and scientific resources between various regions. Cloud computing performance heavily based on job scheduling algorithms that are utilized for queue waiting in modern scientific applications. The researchers are considered cloud computing a popular platform for new enforcements. These scheduling algorithms help in design efficient queue lists in cloud as well as they play vital role in reducing waiting for processing time in cloud computing. A novel job scheduling is proposed in this paper to enhance performance of cloud computing and reduce delay time in queue waiting for jobs. The proposed algorithm tries to avoid some significant challenges that throttle from developing applications of cloud computing. However, a smart scheduling technique is proposed in our paper to improve performance processing in cloud applications. Our experimental result of the proposed job scheduling algorithm shows that the proposed schemes possess outstanding enhancing rates with a reduction in waiting time for jobs in queue list.

show abstract

Section: Min-min Algorithmmentioning

confidence: 99%