作者
Mbarka Soualhia, Foutse Khomh, Sofiène Tahar
发表日期
2017/12/1
来源
Journal of Systems and Software
卷号
134
页码范围
170-189
出版商
Elsevier
简介
Context: Hadoop, Spark, Storm, and Mesos are very well known frameworks in both research and industrial communities that allow expressing and processing distributed computations on massive amounts of data. Multiple scheduling algorithms have been proposed to ensure that short interactive jobs, large batch jobs, and guaranteed-capacity production jobs running on these frameworks can deliver results quickly while maintaining a high throughput. However, only a few works have examined the effectiveness of these algorithms.
Objective: The Evidence-based Software Engineering (EBSE) paradigm and its core tool, i.e., the Systematic Literature Review (SLR), have been introduced to the Software Engineering community in 2004 to help researchers systematically and objectively gather and aggregate research evidences about different topics. In this paper, we conduct a SLR of task scheduling algorithms that …
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