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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2019.6
- 수록면
- 193 - 202 (10page)
- DOI
- 10.7232/JKIIE.2019.45.3.193
이용수
초록· 키워드
오류제보하기
A semi-open queueing network is considered. The network of an arbitrary topology consists of a finite number of nodes operation of which is modeled by single-server queueing systems with a buffer and an exponential service time distribution. Customers arrive at the network according to a Markovian arrival process. The total number of customers, which can be processed simultaneously, is restricted by a fixed in advance threshold. If the number of customers in the network at a new customer arrival moment is less than the threshold, this customer is admitted for service. Otherwise, the customer temporarily leaves the system (it is said that the customer joins the orbit) and retries to get access to the network after the random time intervals duration of which has an exponential distribution. The capacity of the orbit is infinite. After the admission to the network, the customer starts sequential service in a random number of nodes. The choice of the first and the subsequent nodes for service is made stochastically according to a fixed stochastic vector and a transition probability matrix. The behavior of the network is described by the continuous-time Markov chain that belongs to the class of asymptotically quasi-Toeplitz Markov chains. This allows to derive a transparent condition for the ergodicity of the chain and compute its steady-state distribution. Expressions for computation of various performance measures of the network are derived. Numerical results are presented. The model can be applied, e.g., for analysis and optimization of the operation of logistics and manufacturing systems, and the wireless telecommunication networks. To the best of our knowledge, queueing networks with correlated arrival flows and retrials are not considered in the existing literature.
목차
1. Introduction
2. Mathematical Model
3. Process of System States
4. Ergodicity Condition
5. Performance Measures
6. Numerical Examples
7. Conclusion
References
참고문헌 (21)
참고문헌 신청
Balsamo, S. (2000), Product form queueing networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1769, 377-401.
Artalejo, J. R. and Gomez-Corral, A. (2008), Retrial queueing systems : A computational approach, Berlin-Heidelberg, Springer.
Chakravarthy, S. R. (2001), The batch Markovian arrival process : a review and future work, in : A. Krishnamoorthy, N. Raju, V. Ramaswami (Eds.), Advances in Probability Theory and Stochastic Processes, Notable Publications Inc., New Jersey, 21-29.
Dallery, Y. (1990), Approximate analysis of general open queuing networks with restricted capacity, Performance Evaluation, 11(3), 209-222.
Denning, P. J. and Buzen, J. P. (1978), The Operational Analysis of Queueing Network Models, Computing Surveys, 10, 225-261.
Artalejo, J. R. and Gomez-Corral, A. (2008), Retrial queueing systems : A computational approach, Berlin-Heidelberg, Springer.
Chakravarthy, S. R. (2001), The batch Markovian arrival process : a review and future work, in : A. Krishnamoorthy, N. Raju, V. Ramaswami (Eds.), Advances in Probability Theory and Stochastic Processes, Notable Publications Inc., New Jersey, 21-29.
Dallery, Y. (1990), Approximate analysis of general open queuing networks with restricted capacity, Performance Evaluation, 11(3), 209-222.
Denning, P. J. and Buzen, J. P. (1978), The Operational Analysis of Queueing Network Models, Computing Surveys, 10, 225-261.
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UCI(KEPA) : I410-ECN-0101-2019-530-000758758