Markov model of composite queueing systems

Asymptotic analysis of multidimensional

Asymptotic analysis of multidimensional characteristics of Markov queueing systems

✍ V. V. Anisimov; L. I. Lukashuk 📂 Article 📅 1984 🏛 Springer US 🌐 English ⚖ 675 KB

Markov Skeleton Processes and Applicatio

Markov Skeleton Processes and Applications to Queueing Systems

✍ Zhen-ting Hou 📂 Article 📅 2002 🏛 Institute of Applied Mathematics, Chinese Academy 🌐 English ⚖ 225 KB

Queueing Modelling Fundamentals || Marko

Queueing Modelling Fundamentals || Markov-Modulated Arrival Process

✍ Ng, Chee-Hock; Soong, Boon-Hee 📂 Article 📅 2008 🏛 John Wiley & Sons, Ltd 🌐 English ⚖ 236 KB 👁 2 views

Queueing analysis is a vital tool used in the evaluation of system performance. Applications of queueing analysis cover a wide spectrum from bank automated teller machines to transportation and communications data networks. Fully revised, this second edition of a popular book contains the significa

Markov-modulated finite-source queueing

Markov-modulated finite-source queueing models in evaluation of computer and communication systems

✍ J. Sztrik; C.S. Kim 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 509 KB

Queueing Modelling Fundamentals || Discr

Queueing Modelling Fundamentals || Discrete and Continuous Markov Processes

✍ Ng, Chee-Hock; Soong, Boon-Hee 📂 Article 📅 2008 🏛 John Wiley & Sons, Ltd 🌐 English ⚖ 223 KB 👁 2 views

Queueing analysis is a vital tool used in the evaluation of system performance. Applications of queueing analysis cover a wide spectrum from bank automated teller machines to transportation and communications data networks. Fully revised, this second edition of a popular book contains the significa

Queue length distributions in a markov m

Queue length distributions in a markov model of a multistage clocked queueing network

✍ Ora E. Percus; J. K. Percus 📂 Article 📅 1990 🏛 John Wiley and Sons 🌐 English ⚖ 265 KB

In (41, we treated the problem of passage through a discrete-time clock-regulated multistage queueing network by modeling the input time series (a,,) to each queue as a Markov chain. We showed how to transform probability transition information from the input of one queue to the input of the next in