Adventures in stochastic processes
Adventures in stochastic processes
Stochastic geometry models of mobile communication networks
Frontiers in queueing
Modeling and analysis of stochastic systems
Modeling and analysis of stochastic systems
Mathematics of Operations Research
An intergrated traffic model for multimedia wireless networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - 01/14/2002
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Control and recovery from rare congestion events in a large multi-server system
Queueing Systems: Theory and Applications
On a Queueing NetWork Model for Cellular Mobile Telecommunications Networks
Operations Research
New call blocking versus handoff blocking in cellular networks
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 1
Dynamic staffing in a telephone call center aiming to immediately answer all calls
Operations Research Letters
User mobility modeling and characterization of mobility patterns
IEEE Journal on Selected Areas in Communications
| Hi-index | 0.00 |
We propose a queueing network model which can be used for the integration of the mobility and teletraffic aspects that are characteristic of wireless networks. In the general case, the model is an open network of infinite server queues where customers arrive according to a non-homogeneous Poisson process. The movement of a customer in the network is described by a Markov renewal process. Moreover, customers have attributes, such as a teletraffic state, that are driven by continuous time Markov chains and, therefore, change as they move through the network. We investigate the transient and limit number of customers in disjoint sets of nodes and attributes. These turn out to be independent Poisson random variables. We also calculate the covariances of the number of customers in two sets of nodes and attributes at different time epochs. Moreover, we conclude that the arrival process per attribute to a node is the sum of independent Poisson cluster processes and derive its univariate probability generating function. In addition, the arrival process to an outside node of the network is a non-homogeneous Poisson process. We illustrate the applications of the queueing network model and the results derived in a particular wireless network.