Statistical Monitoring of Queuing Networks

Queuing systems are important parts of our daily lives and to keep their operations at an efficient level they need to be monitored by using queuing Performance Metrics, such as average queue lengths and average waiting times. On the other hand queue lengths and waiting ti...

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Main Author: Kaya, Yaren Bilge
Format: Others
Published: Scholar Commons 2018
Subjects:
Online Access:https://scholarcommons.usf.edu/etd/7534
https://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=8731&context=etd
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spelling ndltd-USF-oai-scholarcommons.usf.edu-etd-87312019-10-04T05:06:14Z Statistical Monitoring of Queuing Networks Kaya, Yaren Bilge Queuing systems are important parts of our daily lives and to keep their operations at an efficient level they need to be monitored by using queuing Performance Metrics, such as average queue lengths and average waiting times. On the other hand queue lengths and waiting times are generally random variables and their distributions depend on different properties like arrival rates, service times, number of servers. We focused on detecting the change in service rates in this report. Therefore, we monitored queues by using Cumulative Sum(CUSUM) charts based on likelihood ratios and compared the Average Run Length values of different service rates. 2018-10-26T07:00:00Z text application/pdf https://scholarcommons.usf.edu/etd/7534 https://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=8731&context=etd Graduate Theses and Dissertations Scholar Commons CUSUM Charts Jackson's networks Queuing analysis Markov Chain Statistical Process Control Industrial Engineering
collection NDLTD
format Others
sources NDLTD
topic CUSUM Charts
Jackson's networks
Queuing analysis
Markov Chain Statistical Process Control
Industrial Engineering
spellingShingle CUSUM Charts
Jackson's networks
Queuing analysis
Markov Chain Statistical Process Control
Industrial Engineering
Kaya, Yaren Bilge
Statistical Monitoring of Queuing Networks
description Queuing systems are important parts of our daily lives and to keep their operations at an efficient level they need to be monitored by using queuing Performance Metrics, such as average queue lengths and average waiting times. On the other hand queue lengths and waiting times are generally random variables and their distributions depend on different properties like arrival rates, service times, number of servers. We focused on detecting the change in service rates in this report. Therefore, we monitored queues by using Cumulative Sum(CUSUM) charts based on likelihood ratios and compared the Average Run Length values of different service rates.
author Kaya, Yaren Bilge
author_facet Kaya, Yaren Bilge
author_sort Kaya, Yaren Bilge
title Statistical Monitoring of Queuing Networks
title_short Statistical Monitoring of Queuing Networks
title_full Statistical Monitoring of Queuing Networks
title_fullStr Statistical Monitoring of Queuing Networks
title_full_unstemmed Statistical Monitoring of Queuing Networks
title_sort statistical monitoring of queuing networks
publisher Scholar Commons
publishDate 2018
url https://scholarcommons.usf.edu/etd/7534
https://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=8731&context=etd
work_keys_str_mv AT kayayarenbilge statisticalmonitoringofqueuingnetworks
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