Titlebook: Introduction to Stochastic Networks; Richard Serfozo Book 1999 Springer Science+Business Media New York 1999 BCMP network.Computer.Jackson

TUMOR

書目名稱Introduction to Stochastic Networks影響因子(影響力)




書目名稱Introduction to Stochastic Networks影響因子(影響力)學科排名




書目名稱Introduction to Stochastic Networks網絡公開度




書目名稱Introduction to Stochastic Networks網絡公開度學科排名




書目名稱Introduction to Stochastic Networks被引頻次




書目名稱Introduction to Stochastic Networks被引頻次學科排名




書目名稱Introduction to Stochastic Networks年度引用




書目名稱Introduction to Stochastic Networks年度引用學科排名




書目名稱Introduction to Stochastic Networks讀者反饋




書目名稱Introduction to Stochastic Networks讀者反饋學科排名

gonioscopy

Reversible Processes, expected number of the transitions in the reverse order. This is also equivalent to a time-reversibility property that, at any instant, the future of the process is stochastically indistinguishable from viewing the process in reverse time. A remarkable feature of such a process is that its equilibr

勉強

Miscellaneous Networks,e processes to model networks with multiple types of units, where the routings and services may depend on a customer’s type. This includes Kelly networks with deterministic routes for units, and BCMP networks with Cox and general service times depending on a unit’s type. We also discuss several form

Overdose

貝雷帽

Little Laws,ttle law. Specifically, a Little law for a service system says that the average sojourn time . of a customer in the system and the average queue length . of the system are related by . = λ., where λ is the average arrival rate of units to the system. This fundamental relation is a . or law of large

MOT

Stationary Systems,ulus and Campbell—Mecke formulas for functionals of stationary systems. This material is the foundation for modeling networks and queueing systems with stationary dynamics, and for obtaining Little laws for such systems.

含糊

Longitude

低能兒

,Space—Time Poisson Models,the collective movement of units or customers in space and time, where the units enter the system according to a Poisson space—time process and then move about independently of each other. Because of these properties, the evolution of the system can be formulated by certain “random transformations”

動作謎

Spatial Queueing Systems, or a general space. The state of such a system is a point process on a space that evolves over time as a “measure-valued” Markov jump process. Each unit moves in the space according to a Markovian routing mechanism and it receives services at the locations it visits. The service times are exponenti