An overview of statistical and information-theoretic aspects of hidden Markov processes
(HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain …

Marked point processes (MPP's) play an important role in stochastic modeling. In this talk we
review a class of point processes, called batch Markovian arrival processes (BMAP's), that is …

The versatile Markovian point process was introduced by MF Neuts in 1979. This is a rich
class of point processes whichcontains many familiar arrival process as very special cases …

Point processes whose arrival rates vary randomly over time arise in many applications of
interest, notably in communications modeling. The Markov-modulated Poisson process has …

We study the performance of a statistical multiplexer whose inputs consist of a superposition
of packetized voice sources and data. The performance analysis predicts voice packet delay …

This paper analyzes a model of a multiplexer for packetized voice and data. A major part of
the analysis is devoted to characterizing the aggregate packet arrival process resulting from …

We present an overview of recent results related to the single server queue with general
independent and identically distributed service times and a batch Markovian arrival process …

The performance of single-server queues with independent interarrival intervals and service
demands is well understood, and often analytically tractable. In particular, the M/M/1 queue …

Software-Defined Networking (SDN) is an emerging architecture for the next-generation
Internet, providing unprecedented network programmability to handle the explosive growth …

We start with the premise, and provide evidence that it is valid, that a Markov-modulated
Poisson process (MMPP) is a good model for Internet traffic at the packet/byte level. We …