A Class of Data Traffic Processes-Covariance Function Characterization and Related Queuing Results

Abstract

While the "call" or "session" is the basic entity that is set up in many data traffic applications, the performance analysis of data network elements depends on the internal units of traffic into which calls are decomposed.In a packet-switching network, the packet represents the basic internal unit of traffic, and packets from different calls time-share facilities and contend for network resources, giving rise to queuing delays. In this paper, we consider the problem of characterizing the doubly stochastic packet process resulting from a superposition of call types, each type having a stochastically varying number of calls in progress.We obtain statistical properties of the process and use them to obtain an approximating process, based in part upon time constants associated with the packet-rate covariance function. We discuss existing queuing models dealing with this ap proximating class of inputs and present results showing the effect of call and packet traffic parameters on queuing performance.

An analytical model for on-chip interconnects in multimedia embedded systems

“…In this paper, the arrival process of multimedia traffic is represented by an MMPP [Fischer and Meier-Hellstern 1993], which is a doubly stochastic process with the arrival rate varying according to a multi-state ergodic continuous-time Markov chain. The two-state MMPP has been widely used in numerous studies to model the message arrival behaviour of bursty traffic due to the following reasons: 1) many studies [Heffes 1980;Liu et al 2008;Shah-Heydari and Le-Ngoc 2000] have revealed that MMPP has the ability of capturing the time-varying arrival rate and the important correlations among inter-arrival times of multimedia traffic; 2) MMPP is closed under the splitting and superposition operations and thus can be used to model the decomposition and superposition of network traffic in on-chip interconnection networks; and 3) the queueing-related results of MMPP have been widely studied [Fischer and Meier-Hellstern 1993;Heffes 1980], which makes the solutions of modelling networks with the MMPP arrival process analytically tractable. In this study, a two-state s MMPP is adopted to model the traffic burstiness of the message arrival process generated by the source node [Wu et al 2011 [Heffes 1980;Min and Ould-Khaoua 2004].…”

Distributed Data Transaction of an Apache Web Server using Bulk Service Rule

“…[14].The number of systems "K" is the model, we use the some parameter that were found. [15]. Where a similar model was used with PDP arrivals instead of MMPP arrivals.…”

Novel Mechanism Control Algorithm for Wired Network

“…A TCP/IP connection is timed out at the client computer (request) when it will take a long time to the server to return (acknowledge) (Bause et al, 1994) The number of systems 'N' is the model; we use the some parameters that were found (Heffes, 1978). Where a similar model was used with MPDP arrivals instead of MMPP arrivals.…”