| DATE: 
        Thursday, February 16, 2006TIME: 
        Noon - 1 pm
 PLACE: 
        CIC 2101
  SPEAKER: 
        Adam 
        Wierman
 CMU
 TITLE: 
        Open vs. Closed: A Cautionary Tale
 ABSTRACT: 
        Every systems researcher is well aware of the importance of setting up 
        one's experiments so that the system being modeled is "accurately 
        represented." Fundamental to this is using a realistic workload generator 
        that accurately models the service request demands, popularity distribution, 
        etc. One particularly important aspect of a workload generator that is 
        not given the attention it deserves is whether the workload generator 
        uses an open or closed system model. Using a combination of implementation 
        and simulation experiments, we will illustrate that there is a vast difference 
        in behavior between the open and closed system models in realistic settings, 
        even when all other workload parameters are held fixed. These results 
        illustrate that understanding the appropriate system model for a given 
        application is essential to evaluating the impact of design decisions, 
        e.g. proposed changes in the scheduling policy used. Thus, we will also 
        provide guidelines for determining when open and closed system models 
        are appropriate.
 BIO: 
        Adam Wierman is currently a doctoral student at Carnegie Mellon University. 
        He received a BS with University Honors in Computer science and Mathematics 
        with minors in Psychology and Statistics from Carnegie Mellon University 
        in 2001. He is a recipient of the NSF Graduate Research Fellowship, the 
        best student paper award at the ACM Sigmetrics conference, and multiple 
        teaching awards, including the Alan J. Perlis Student Teaching Award. 
        He currently works on the analysis of scheduling policies for queuing 
        systems. His main focus is on understanding the impact of scheduling techniques 
        and heuristics on efficiency and fairness metrics.
       
       For Further 
        Seminar Info: ,
 
         
        or visit  http://www.pdl.cmu.edu/SDI/
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