Scheduling in the Presence of Data Intensive Compute Jobs

We study the performance of non-adaptive scheduling policies in computing systems with multiple servers. Compute jobs are mostly regular, with modest service requirements. However, there are sporadic data intensive jobs, whose expected service time is much higher than that of the regular jobs. For t...

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Bibliographic Details
Published in2019 IEEE International Conference on Big Data (Big Data) pp. 5989 - 5991
Main Authors Behrouzi-Far, Amir, Soljanin, Emina
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2019
Subjects
Load management
Optimal scheduling
Processor scheduling
Random variables
Redundancy
Resource description framework
Servers
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Summary:We study the performance of non-adaptive scheduling policies in computing systems with multiple servers. Compute jobs are mostly regular, with modest service requirements. However, there are sporadic data intensive jobs, whose expected service time is much higher than that of the regular jobs. For this model, we are interested in the effect of scheduling policies on the average time a job spends in the system. To this end, we introduce two performance indicators in a simplified, only-arrival system. We believe that these performance indicators are good predictors of the relative performance of the policies in the queuing system, which is supported by simulations results.
DOI:10.1109/BigData47090.2019.9006369