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            <title xml:lang="en">IBB: Improved K-Resource Aware Backfill Balanced Scheduling for HTCondor</title>
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                <forename type="first">Lan</forename>
                <surname>Liu</surname>
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            <idno type="halRefHtml">&lt;i&gt;13th IFIP International Conference on Network and Parallel Computing (NPC)&lt;/i&gt;, Oct 2016, Xi'an, China. pp.85-92, &lt;a target="_blank" href="https://dx.doi.org/10.1007/978-3-319-47099-3_7"&gt;&amp;#x27E8;10.1007/978-3-319-47099-3_7&amp;#x27E9;&lt;/a&gt;</idno>
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                <title xml:lang="en">IBB: Improved K-Resource Aware Backfill Balanced Scheduling for HTCondor</title>
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                    <forename type="first">Lan</forename>
                    <surname>Liu</surname>
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                    <forename type="first">Zhongzhi</forename>
                    <surname>Luan</surname>
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                    <forename type="first">Haozhan</forename>
                    <surname>Wang</surname>
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                    <forename type="first">Depei</forename>
                    <surname>Qian</surname>
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                <title level="m">Lecture Notes in Computer Science</title>
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                  <title>13th IFIP International Conference on Network and Parallel Computing (NPC)</title>
                  <date type="start">2016-10-28</date>
                  <date type="end">2016-10-29</date>
                  <settlement>Xi'an</settlement>
                  <country key="CN">China</country>
                </meeting>
                <editor>Guang R. Gao</editor>
                <editor>Depei Qian</editor>
                <editor>Xinbo Gao</editor>
                <editor>Barbara Chapman</editor>
                <editor>Wenguang Chen</editor>
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                  <publisher>Springer International Publishing</publisher>
                  <biblScope unit="serie">Network and Parallel Computing</biblScope>
                  <biblScope unit="volume">LNCS-9966</biblScope>
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              <p>HTCondor, a batch system characterized by its matchmaking mechanism, schedules job in FCFS way, so its performance is not ideal as expected. Backfilling is a technique to address the above problem. Most backfilling algorithms are based on CPU information and have large room for improvements with considering other resource information. The K-resource aware scheduling algorithm Backfill Balanced (BB) selects backfill job which can best balance the usage of all resources and achieve better performance compared with the classical backfilling algorithm. However, BB does not realize that small jobs’ impacts on resource utilization are negligible and they mainly contribute to reduce the average response time. Here we propose the IBB algorithm, which utilizes the characteristics of small jobs to guide a better job selection. We implemented IBB on HTCondor to improve its performance. Experiments results show that IBB can provide up to 60 % performance gains in most performance metrics compared with BB.</p>
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              <addrLine>Beijing 100083 PR China</addrLine>
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