Abstract: In this paper, we study statistical multiplexing of VBR
video in ATM networks. ATM promises to provide high speed realtime
multi-point to central video transmission for telemedicine
applications in rural hospitals and in emergency medical services.
Video coders are known to produce variable bit rate (VBR) signals
and the effects of aggregating these VBR signals need to be
determined in order to design a telemedicine network infrastructure
capable of carrying these signals. We first model the VBR video
signal and simulate it using a generic continuous-data autoregressive
(AR) scheme. We carry out the queueing analysis by the Fluid
Approximation Model (FAM) and the Markov Modulated Poisson
Process (MMPP). The study has shown a trade off: multiplexing
VBR signals reduces burstiness and improves resource utilization,
however, the buffer size needs to be increased with an associated
economic cost. We also show that the MMPP model and the Fluid
Approximation model fit best, respectively, the cell region and the
burst region. Therefore, a hybrid MMPP and FAM completely
characterizes the overall performance of the ATM statistical
multiplexer. The ramifications of this technology are clear: speed,
reliability (lower loss rate and jitter), and increased capacity in video
transmission for telemedicine. With migration to full IP-based
networks still a long way to achieving both high speed and high
quality of service, the proposed ATM architecture will remain of
significant use for telemedicine.
Abstract: This paper reports the feasibility of the ARMA model
to describe a bursty video source transmitting over a AAL5 ATM link
(VBR traffic). The traffic represents the activity of the action movie
"Lethal Weapon 3" transmitted over the ATM network using the Fore
System AVA-200 ATM video codec with a peak rate of 100 Mbps
and a frame rate of 25. The model parameters were estimated for a
single video source and independently multiplexed video sources. It
was found that the model ARMA (2, 4) is well-suited for the real data
in terms of average rate traffic profile, probability density function,
autocorrelation function, burstiness measure, and the pole-zero
distribution of the filter model.
Abstract: Stochastic modeling of network traffic is an area of
significant research activity for current and future broadband
communication networks. Multimedia traffic is statistically
characterized by a bursty variable bit rate (VBR) profile. In this
paper, we develop an improved model for uniform activity level
video sources in ATM using a doubly stochastic autoregressive
model driven by an underlying spatial point process. We then
examine a number of burstiness metrics such as the peak-to-average
ratio (PAR), the temporal autocovariance function (ACF) and the
traffic measurements histogram. We found that the former measure is
most suitable for capturing the burstiness of single scene video
traffic. In the last phase of this work, we analyse statistical
multiplexing of several constant scene video sources. This proved,
expectedly, to be advantageous with respect to reducing the
burstiness of the traffic, as long as the sources are statistically
independent. We observed that the burstiness was rapidly
diminishing, with the largest gain occuring when only around 5
sources are multiplexed. The novel model used in this paper for
characterizing uniform activity video was thus found to be an
accurate model.
Abstract: High speed networks provide realtime variable bit rate
service with diversified traffic flow characteristics and quality
requirements. The variable bit rate traffic has stringent delay and
packet loss requirements. The burstiness of the correlated traffic
makes dynamic buffer management highly desirable to satisfy the
Quality of Service (QoS) requirements. This paper presents an
algorithm for optimization of adaptive buffer allocation scheme for
traffic based on loss of consecutive packets in data-stream and buffer
occupancy level. Buffer is designed to allow the input traffic to be
partitioned into different priority classes and based on the input
traffic behavior it controls the threshold dynamically. This algorithm
allows input packets to enter into buffer if its occupancy level is less
than the threshold value for priority of that packet. The threshold is
dynamically varied in runtime based on packet loss behavior. The
simulation is run for two priority classes of the input traffic –
realtime and non-realtime classes. The simulation results show that
Adaptive Partial Buffer Sharing (ADPBS) has better performance
than Static Partial Buffer Sharing (SPBS) and First In First Out
(FIFO) queue under the same traffic conditions.