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<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>Aviv Zohar</author_name><author_url>https://www.microsoft.com/en-us/research/people/avivz/</author_url><title>Competing Schedulers - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="zENMeV36LT"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/competing-schedulers/"&gt;Competing Schedulers&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/competing-schedulers/embed/#?secret=zENMeV36LT" width="600" height="338" title="&#x201C;Competing Schedulers&#x201D; &#x2014; Microsoft Research" data-secret="zENMeV36LT" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>Previous work on machine scheduling has considered the case of agents who control the scheduled jobs and attempt to minimize their own completion time. We argue that in cloud and grid computing settings, different machines cannot be considered to be fully cooperative as they may belong to competing economic entities, and that agents can easily [&hellip;]</description></oembed>
