MQWAGS: Research on Job Scheduling Algorithms Based on Cloud Computing
Authors: 
Gang Qiu, Liping Jiang, Yajun ZhangAuthors Info & Claims
Pages 42 - 48
Abstract
With the rapid development of digital technology, from the application of traditional databases and scientific computing to the emerging cloud computing services, the analysis, and processing of massive data has become the focus of society. Providing low-cost, scalable, and configurable shared cloud services to users on cloud service platforms is a new hotspot for the development of major cloud service providers. Job scheduling plays an important role in improving the overall system performance of cloud service capabilities. Simple job scheduling strategies (such as Fair and FIFO scheduling) do not consider job size and may degrade performance when jobs of different sizes arrive. This paper proposes the MQWAG (Multi-Queue Load-Sensitive Greedy Scheduling Algorithm) job scheduling algorithm to reorder multi-queue jobs so that short jobs are executed preferentially in multiple queues. In our experiments, our algorithm shortened the average job completion time by about 26% compared with other algorithms.
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- MQWAGS: Research on Job Scheduling Algorithms Based on Cloud Computing
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Research on Job Scheduling Algorithms Based on Cloud Computing
Green, Pervasive, and Cloud ComputingAbstractWith the rapid development of digital technology, from the application of traditional databases and scientific computing to the emerging cloud computing services, the analysis and processing of massive data has become the focus of society. ...
Modified Rate-Monotonic Algorithm for Scheduling Periodic Jobs with Deferred Deadlines
The deadline of a request is the time instant at which its execution must complete. The deadline of the request in any period of a job with deferred deadline is some time instant after the end of the period. The authors describe a semi-static priority-...
SG-PBFS: Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
AbstractJob scheduling in cloud computing plays a crucial role in optimizing resource utilization and ensuring efficient job allocation. But cloud resources may be wasted, or service performance may suffer because of under-utilization or over-utilization ...
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Published In
July 2020
276 pages
ISBN:9781450375603
DOI:10.1145/3409501
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- Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 25 August 2020
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