{"title":"离散时间队列的动态控制策略","authors":"Tsung-Yin Wang, Fu-Min Chang","doi":"10.1504/IJSOI.2016.080074","DOIUrl":null,"url":null,"abstract":"In queueing system, when the server is idle, one of control policy for determining the timing of server activated is when a fixed number N of customers accumulates for service in the system. However, on some practical situations such as watching video file online, the threshold value N may vary depending on different situations. For such situation, this paper studies a random N-policy Geo/G/1 queue, where N is determined as each new cycle begins. We derive some system characteristics, such as system size, idle period, busy period and sojourn time, by using the probability generating function and supplementary variable technique. We also prove that the system size of a continuous-time random N-policy M/G/1 queue can be approximated by the presented discrete-time model.","PeriodicalId":35046,"journal":{"name":"International Journal of Services Operations and Informatics","volume":"8 1","pages":"79"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJSOI.2016.080074","citationCount":"1","resultStr":"{\"title\":\"Dynamic control policy for the discrete-time queue\",\"authors\":\"Tsung-Yin Wang, Fu-Min Chang\",\"doi\":\"10.1504/IJSOI.2016.080074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In queueing system, when the server is idle, one of control policy for determining the timing of server activated is when a fixed number N of customers accumulates for service in the system. However, on some practical situations such as watching video file online, the threshold value N may vary depending on different situations. For such situation, this paper studies a random N-policy Geo/G/1 queue, where N is determined as each new cycle begins. We derive some system characteristics, such as system size, idle period, busy period and sojourn time, by using the probability generating function and supplementary variable technique. We also prove that the system size of a continuous-time random N-policy M/G/1 queue can be approximated by the presented discrete-time model.\",\"PeriodicalId\":35046,\"journal\":{\"name\":\"International Journal of Services Operations and Informatics\",\"volume\":\"8 1\",\"pages\":\"79\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1504/IJSOI.2016.080074\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Services Operations and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJSOI.2016.080074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Business, Management and Accounting\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Services Operations and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJSOI.2016.080074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
Dynamic control policy for the discrete-time queue
In queueing system, when the server is idle, one of control policy for determining the timing of server activated is when a fixed number N of customers accumulates for service in the system. However, on some practical situations such as watching video file online, the threshold value N may vary depending on different situations. For such situation, this paper studies a random N-policy Geo/G/1 queue, where N is determined as each new cycle begins. We derive some system characteristics, such as system size, idle period, busy period and sojourn time, by using the probability generating function and supplementary variable technique. We also prove that the system size of a continuous-time random N-policy M/G/1 queue can be approximated by the presented discrete-time model.
期刊介绍:
The advances in distributed computing and networks make it possible to link people, heterogeneous service providers and physically isolated services efficiently and cost-effectively. As the economic dynamics and the complexity of service operations continue to increase, it becomes a critical challenge to leverage information technology in achieving world-class quality and productivity in the production and delivery of physical goods and services. The IJSOI, a fully refereed journal, provides the primary forum for both academic and industry researchers and practitioners to propose and foster discussion on state-of-the-art research and development in the areas of service operations and the role of informatics towards improving their efficiency and competitiveness.