DTIC ADA361701: Analysis Of A Non-Trivial Queueing Network - Info and Reading Options
By Defense Technical Information Center
"DTIC ADA361701: Analysis Of A Non-Trivial Queueing Network" and the language of the book is English.
“DTIC ADA361701: Analysis Of A Non-Trivial Queueing Network” Metadata:
- Title: ➤ DTIC ADA361701: Analysis Of A Non-Trivial Queueing Network
- Author: ➤ Defense Technical Information Center
- Language: English
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- Internet Archive ID: DTIC_ADA361701
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"DTIC ADA361701: Analysis Of A Non-Trivial Queueing Network" Description:
The Internet Archive:
In studying complex queueing networks, one generally seeks to employ exact analytic solutions to reduce burden on computational resources. Barring the existence of an exact solution, the alternatives include approximation techniques and simulation. Approximation is the more attractive alternative from a time and effort perspective; however, cases exist that are not amiable to this technique. This work increases the flexibility of approximation techniques in obtaining estimates of congestion measures for complex, open queueing networks having several customer classes and class-dependent structures. We accomplish this by providing the procedure to aggregate multiple classes into a single class in order to apply an existing approximation technique. The resulting method is shown to yield good agreement with results obtained by simulation. The immediate application of this work is as a tool to focus a simulation study of multi-class queueing networks. For large networks, reasonable performance estimates can be obtained quickly. Once the basic input parameters are determined, different scenarios may be rapidly evaluated in a fraction of the time needed to modify a typical simulation model. This allows one to check ideas and determine where to invest time and funding when constructing a simulation model to obtain performance estimates on a by-class basis.
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"DTIC ADA361701: Analysis Of A Non-Trivial Queueing Network" is available for download from The Internet Archive in "texts" format, the size of the file-s is: 124.64 Mbs, and the file-s went public at Sun Apr 22 2018.
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