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  <title><![CDATA[PhD Defense by Yuan Li]]></title>
  <body><![CDATA[<p>Title:&nbsp;Stochastic Comparison Approach to Multi-server Queues: Bounds, Heavy Tails, and Large Deviations</p>

<p>&nbsp;</p>

<p>Advisors: Dr. David Goldberg</p>

<p>&nbsp;</p>

<p>Committee members:</p>

<p>Dr.&nbsp;Robert Foley</p>

<p>Dr.&nbsp;Hayriye Ayhan</p>

<p>Dr.&nbsp;Siva Theja Maguluri&nbsp;</p>

<p>Dr.&nbsp;Jun Xu</p>

<p>&nbsp;</p>

<p>Date and Time:&nbsp;<strong>May 9th (Tuesday), 2017, at 11:00 AM</strong></p>

<p>Location:&nbsp;ISyE&nbsp;<strong>Main</strong>&nbsp;Building Room&nbsp;<strong>228</strong>&nbsp;-&nbsp;Executive Classroom</p>

<p>&nbsp;</p>

<p>Summary:</p>

<p>&nbsp;</p>

<p>For a FCFS&nbsp;<strong>GI/GI/n</strong>&nbsp;model queue, when the number of servers&nbsp;<strong>n</strong>&nbsp;is large, the direct analysis of various performance metrics is generally analytically intractable. Therefore methods like developing bounds and heavy-traffic approximation are crucial to help us understand the system. A particularly popular heavy-traffic regime is the so-called Halfin-Whitt regime, under which the number of servers&nbsp;<strong>n</strong>&nbsp;grows large and the traffic intensity&nbsp;<strong>&rho;&nbsp;</strong>converges to unity simultaneously under some square-root staffing rule, allowing the system to strike a balance between quality and efficiency. However, all known bounds for general multi-server queues in this setting suffer from several fundamental shortcomings, such as holding only asymptotically or involving non-explicit constants. &nbsp;Furthermore, even less is known in the presence of heavy-tailed distributions in the model. This thesis primarily addresses these problems.&nbsp;</p>

<p>&nbsp;</p>

<p>In the first part of this thesis, we consider the FCFS <strong>GI/GI/n</strong> queue, and prove the first simple and explicit bounds that scale gracefully and universally as <strong>1/(1-</strong><strong>&rho;)</strong>, across all notions of heavy traffic, including both the classical and Halfin-Whitt settings. In particular, supposing that the inter-arrival and service times, distributed as random variables <strong>A</strong> and <strong>S</strong>, have finite <strong>r</strong>th moment for some <strong>r &gt; 2</strong>, and letting&nbsp;<strong>&mu;_A</strong>&nbsp;(<strong>&mu;_S</strong>) denote <strong>1/E[A]</strong> (<strong>1/E[S]</strong>), our main results are bounds for the tail of the steady-state queue length and the steady-state probability of delay, expressed as simple and explicit functions of only <strong>E[(A&mu;_A)^r]</strong>, <strong>&nbsp;E[(S&mu;_S)^r]</strong>, <strong>r</strong>, and&nbsp;<strong>1/(1-</strong><strong>&rho;)</strong>.</p>

<p>&nbsp;</p>

<p>In the second part of this thesis, we consider the FCFS <strong>GI/GI/n</strong> queue in the Halfin-Whitt heavy traffic regime, in the presence of heavy-tailed distributions. &nbsp;We prove that when service times have finite <strong>1 +&nbsp;&epsilon;</strong>&nbsp;moment for some&nbsp;<strong>&epsilon;&nbsp;&gt; 0</strong> and inter-arrival times have finite second moment, the sequence of stationary queue length distributions, normalized by <strong>n^(1/2)</strong>, is tight in the Halfin-Whitt regime. Furthermore, we develop simple and explicit bounds on the stationary queue length in that regime. For the setting where instead the inter-arrival times have an Pareto tail with index <strong>1&lt;</strong><strong>&alpha;&lt;2</strong>, we extend recent results of&nbsp;<a href="https://projecteuclid.org/euclid.aap/1474296313">[Hurvich and Reed, 2016]</a>, by proving for general service time distribution, the sequence of stationary queue length distributions, normalized by <strong>n^(1/</strong><strong>&alpha;</strong><strong>)</strong>, is tight (under their scaling,&nbsp;which we refer to as the Halfin-Whitt-Reed scaling regime).</p>

<p>&nbsp;</p>

<p>In the third part of this thesis, we further investigate the large deviation behaviors of the limits of the sequence of scaled stationary queue length in the presence of heavy-tailed inter-arrival and/or service times. When service times have&nbsp;a&nbsp;Pareto tail with index&nbsp;<strong>1&lt;</strong><strong>&alpha;&lt;2</strong>&nbsp;and inter-arrival times have finite second moment, we bound the large deviations behavior of the limiting process and derive a matching lower bound when inter-arrival times are Markovian. &nbsp;We find that the large deviation behavior of the limit has a sub-exponential decay, differing fundamentally from the exponentially decaying tails known to hold in the light-tailed setting. For the setting where instead the inter-arrival times have a Pareto tail with index&nbsp;<strong>1&lt;</strong><strong>&alpha;&lt;2,</strong>&nbsp;we are again able to bound the large-deviations behavior of the&nbsp;limit, and find that our derived bounds do not depend on the particular service time distribution, and are in fact tight even for the case of deterministic service times.</p>
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