Conference PaperPDF Available

An Efficient Scheme for Traffic Management in ATM Networks

Authors:

Abstract and Figures

As ATM network is designed for broad band transmission that is high data rate (25 Mbps to 2.5 Gbps) and supports the transmission of every kind of data, congestion control and delay have been important issues for ATM networks. Data transmission is done in the form of cell (53 bytes) relay. Hence, cell sequence and the error control have to be carried out properly. ATM networks presents difficulties in effectively controlling congestion not found in other types of networks, including frame relay networks. In this paper, we present an efficient methodology for traffic management. The simulation results suggest that the proposed solution is effective for both slow and high data rate transmission.
Content may be subject to copyright.
Abstract As ATM network is designed for broad band
transmission that is high data rate (25 Mbps to 2.5 Gbps) and
supports the transmission of every kind of data, congestion
control and delay have been important issues for ATM networks.
Data transmission is done in the form of cell (53 bytes) relay.
Hence, cell sequence and the error control have to be carried out
properly. ATM networks presents difficulties in effectively
controlling congestion not found in other types of networks,
including frame relay networks. In this paper, we present an
efficient methodology for traffic management. The simulation
results suggest that the proposed solution is effective for both
slow and high data rate transmission.
Keywords— ATM network, broad band transmission, congestion
control, transmission delay
I. INTRODUCTION
International Telecommunication Union (ITU) has
defined a restricted initial set of traffic and congestion control
capacities aiming at simple mechanisms and network
efficiency as follow. That sets the upper bound to the traffic,
variability in the pattern of cell arrival and average rate of
ATM connection.
1. Connection Admission Control.
2. Usage Parameter Control.
3. Priority Control.
4. Fast Resource Management.
5. Selective Cell Discarding.
Apart from that, ATM switch is important network device
in ATM network for congestion and traffic control. That
switches virtual circuit identifier (VCI) from left to right. It
contains buffers and switching circuits to guide the
connections.
A. Problem Statement
Traffic from user nodes can exceed the capacity of the
network, which causes memory buffer of ATM switches to
overflow and data loses. As per high data rate of transmission,
cell storage and traffic management is required in ATM
switches.
The restrictions of ITU-T can be managed by upgrading the
performance of ATM switches. ATM switches takes a time to
process each cell’s VCI through switching circuit and
referring to the routing table instead of no time. That affects
the continuity of the cell transmission.
ATM switches do outgoing buffering if more than one cells
have same VCI, which leads to defer in transmission and
affect the CBR (Constant bit rate). That results in
retransmission or poor performance at receiver side especially
in case of video-audio data.
II. PROPOSED SOLUTION FOR AN EFFICIENT TRAFFIC
MANAGEMENT IN ATM NETWORKS
Small buffers of ATM switches can be replaced with large
memory blocks.
An Efficient Scheme for Traffic Management in
ATM Networks
Syed S. Rizvi1, Aasia Riasat2, Muhammad S. Rashid3, and Khaled M. Elleithy4
Computer Science and Engineering Department, University of Bridgeport1, 3, 4, Bridgeport CT, 06601
Department of Computer Science, Institute of Business Management2, Karachi, Pakistan
{srizvi1, muhammsi3, elleithy4}@bridgeport.edu, aasia.riasat@cbm.edu.pk2
Fig. 1. Switching Architecture
A. Replacing Switching Circuit
ATM switching circuit can be replaced with processing
unit, which has capability of processing cells, just like CPU.
By processing unit cells are transmitted faster or no time and
provides continuous flow of transmission. Routing table is
allocated in memory of processing unit. That does congestion
control and speeds up the transmission of outgoing cells so
that less buffering is required. Due to less buffering and no
data lose, retransmission is not needed to perform.
B. Removing Output Buffers
Another important issue, to fasten the transmission is to
prevent the output buffering. ATM switches buffer the out
going cells, if they have same VCIs. Processing unit can
process those cells at a time that have different VCIs. And the
resulting (outgoing) VCIs of those cells will be different.
Hence, outgoing cells need not to be buffered
III. PROPOSED SOLUTION FOR TRAFFIC MANAGEMENT IN
ATM NETWORKS
A. Scalability
Moreover, if there is higher bandwidth, it is needed to
minimize the buffering. For that, processing unit can be
scaled through transmission in ATM switch. More than one
processing units are implied in ATM switches. At a same
time, more that one cell can be processed. Incoming flow is
divided into the number of channels and assigned to the
processing units having their own memory blocks.
IV. PROPOSED OFFSET MECHANISM IN ROUTING TABLE
Processing unit may take some execution time to access the
outgoing VCI. Instead of searching through whole routing
table, table can be divided into segments having offsets. Each
cell can refer to addressing table to access the offset. And
using that offset outgoing VCI can be defined. Thus, instead
of searching nine rows, each cell has to refer to only three
rows. That way it fasten the access of VCIs and transmission
of cells.
A. Error Control Integration
Secondly, HEC algorithm can be implemented in ATM
switch instead of in receiver. If data is corrupted in cells, that
will be discarded by ATM switches. That results in
improvement of quality of service in transmission.
B. Mathematical Model
CBR of network depends upon the constant duration of
time between arrivals of two subsequent cells to receiver.
Fig. 2. A conventional ATM switch with replacement of switching circuit
Fig. 3. A conventional ATM switch without output buffer
Fig. 4. An scalable ATM switch architecture
PU- processing unit.
RT- routing table.
Mem.- memory block.
That, cell duration is defined as
δ =1/R (1)
Where R= Data rate.
Hence, as data rate is higher, quality of service and CBR can
be improved. And higher cell duration (δ) affects the quality
of service badly.
CBR can be defined as,
CBR C R (2)
Where R= Data rate, C= Channel capacity
Case- 1
Suppose if the velocity of cell across the medium approaches
300 km/s, then the following conclusion can be drawn:
Average holding time of ATM switch with switching
circuit for one cell > 1 s = 1.4 seconds (or more than
transmission medium). This leads us to the following
expression:
That decrease velocity and data rate as, R V
δ 1/R (3)
In (3), we can conclude that the values for δ (cell duration)
will be increased with respect to time. Thus, as ATM switch
with processing unit has less average holding time for cells, it
provides improved quality of service and CBR by formula (2).
Case- 2
Channel capacity of medium is defined as,
C SNR and BER 1/SNR Property (4)
Hence, as we decrease the bit error rate, signal to noise
ratio and channel capacity can be improved. That results in
better quality of service and CBR by formula (2).And as per
the solution, ATM switch with processing unit reduces the bit
error rate by HEC algorithm and by reducing possibility of
retransmission.
V. CONCLUSION
In this paper, we have investigated different architectures
for ATM switches to improve the overall performance of
ATM networks. We have shown that an appropriate
architecture for ATM switch can provide a strong congestion
control which can consequently use to improve the traffic
management in ATM networks. In addition, we described that
how scalable performance can be achieved from the ATM
networks if we deploy offset mechanism in ATM switches.
REFERENCES
[1] Abry, P. & Veitch, D, “Wavelet analysis of long range
dependent traffic,” IEEE Transactions on Information
Theory, Vol. 44, Issue. 1, 1995.
[2] Bjorkman, N., Latour-Henner, A., Hasson, U., Pers, O.,
& Miah, A., “Practical ATM resource dimensioning
based on real-time traffic measurements and analysis,”
GLOBECOM, Vol. 1, pp. 399-403.
[3] Monlar, S. & Vidacs, A., “On modeling and shaping self-
similar ATM traffic,” TR. High speed Networks,
Laboratory, Department of Telecommunications and
Telematics, Technical University of Budapest.
[4] G. Stamoulis, M. Anagostu, and A. Georgantas, “Traffic
source models for ATM networks,” A survey in Computer
Communications, Vol. 17, Issue. 6, pp. 428-438, 1994.
[5] Willinger, W., Taqqu, M.S., Sherman, R. & Wilson,
D.V., “Self-similarity through high variability: Statistical
analysis of Ethernet LAN traffic at the source level,”
IEEE/ACM Transactions on Networking, 2004.
Fig. 5. A proposed approach for offset mechanism for ATM networks in RT
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
A wavelet-based tool for the analysis of long-range dependence and a related semi-parametric estimator of the Hurst parameter is introduced. The estimator is shown to be unbiased under very general conditions, and efficient under Gaussian assumptions. It can be implemented very efficiently allowing the direct analysis of very large data sets, and is highly robust against the presence of deterministic trends, as well as allowing their detection and identification. Statistical, computational, and numerical comparisons are made against traditional estimators including that of Whittle. The estimator is used to perform a thorough analysis of the long-range dependence in Ethernet traffic traces. New features are found with important implications for the choice of valid models for performance evaluation. A study of mono versus multifractality is also performed, and a preliminary study of the stationarity with respect to the Hurst parameter and deterministic trends
Article
Full-text available
A number of recent empirical studies of traffic measurements from a variety of working packet networks have convincingly demonstrated that actual network traffic is self-similar or long-range dependent in nature (i.e., bursty over a wide range of time scales) -- in sharp contrast to commonly made traffic modeling assumptions. In this paper, we provide a plausible physical explanation for the occurrence of self-similarity in LAN traffic. Our explanation is based on new convergence results for processes that exhibit high variability (i.e., infinite variance) and is supported by detailed statistical analyses of real-time traffic measurements from Ethernet LAN's at the level of individual sources. This paper is an extended version of [53] and differs from it in significant ways. In particular, we develop here the mathematical results concerning the superposition of strictly alternating ON/OFF sources. Our key mathematical result states that the superposition of many ON/OFF sources (also k...
Article
Selecting appropriate models of ATM traffic sources is an inportant issue, since it is closely related to the successful design and efficient performance of the ATM networks to be built in the future. For the three basic categories of sources (voice, data and video), numerous source models have been proposed in the literature. In this paper, we summarize the main features of each of these categories, and present a survey of related models. We argue that it is preferable to select a set of standard source models rather than a single such model. We define a set of criteria to be used in the selection, and choose appropriate source models accordingly.
Conference Paper
We have recorded and analysed traffic generated by a set of real ATM terminal implementations running file transfer and desktop conference applications. The measurement data are used to evaluate the resource requirement of each measured implementation. We conclude that currently available ATM terminal equipment indicate a need for very large network element buffers. Finally, we compare two different principles to control the statistics of the generated traffic: ATM traffic shaping and AAL MTU size variation
Article
A number of empirical studies of traffic measurements from a variety of working packet networks have demonstrated that actual network traffic is self-similar or long-range dependent in nature-in sharp contrast to commonly made traffic modeling assumptions. We provide a plausible physical explanation for the occurrence of self-similarity in local-area network (LAN) traffic. Our explanation is based on convergence results for processes that exhibit high variability and is supported by detailed statistical analyzes of real-time traffic measurements from Ethernet LANs at the level of individual sources. This paper is an extended version of Willinger et al. (1995). We develop here the mathematical results concerning the superposition of strictly alternating ON/OFF sources. Our key mathematical result states that the superposition of many ON/OFF sources (also known as packet-trains) with strictly alternating ON- and OFF-periods and whose ON-periods or OFF-periods exhibit the Noah effect produces aggregate network traffic that exhibits the Joseph effect. There is, moreover, a simple relation between the parameters describing the intensities of the Noah effect (high variability) and the Joseph effect (self-similarity). An extensive statistical analysis of high time-resolution Ethernet LAN traffic traces confirms that the data at the level of individual sources or source-destination pairs are consistent with the Noah effect. We also discuss implications of this simple physical explanation for the presence of self-similar traffic patterns in modern high-speed network traffic
On modeling and shaping selfsimilar ATM traffic
  • S Monlar
  • A Vidacs
Monlar, S. & Vidacs, A., "On modeling and shaping selfsimilar ATM traffic," TR. High speed Networks, Laboratory, Department of Telecommunications and Telematics, Technical University of Budapest.
Traffic source models for ATM networks
  • G Stamoulis
  • M Anagostu
  • A Georgantas
G. Stamoulis, M. Anagostu, and A. Georgantas, "Traffic source models for ATM networks," A survey in Computer Communications, Vol. 17, Issue. 6, pp. 428-438, 1994.
5. A proposed approach for offset mechanism for ATM networks in RT
  • Fig
Fig. 5. A proposed approach for offset mechanism for ATM networks in RT