Analytical Modeling of RRM-ATM Switch for Linear Increment and Exponential Decay of Source Data Rate

Mohsen Hosamo,S P Singh,Anand Mohan

doi:10.12691/jcn-4-1-6

Mohsen Hosamo, S P Singh + Show 1 more

Open Access

https://doi.org/10.12691/jcn-4-1-6

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Abstract

This paper describes analytical modeling of relative rate marking (RRM) switch for available bit rate (ABR) ATM service considering linear increment and exponential decay of data rate(s) of the source(s) to achieve faster congestion control of the network through resource management of the RRM switch. Theoretical performance of the switch has been evaluated in respect of link utilization factor and cell loss probability. It is shown that the switch achieves faster control over source(s) along with improved link utilization factor. This is particularly attractive for congestion control in ABR-ATM networks. The developed switch model can find potential application in the design of RRM switch specific to a network environment.

Highlights

Architecture and performance parameters of asynchronous transfer mode (ATM) switches [1,2,3] greatly influence the quality of service (QoS) of ATM networks
relative rate marking (RRM) switches are obvious choice and being extensively used in ATM networks as they can operate with finer resolution and provide a good trade off between the congestion control time and hardware complexity [6,9]
Mars et al used an RRM switch to investigate the performance of transmission control protocol (TCP) connection [7], Lapsley and Rumsewicz [8] discussed advantages and disadvantages of using no increase (NI) bit in the feedback loop to control the source data rate

Summary

Introduction

Architecture and performance parameters of asynchronous transfer mode (ATM) switches [1,2,3] greatly influence the quality of service (QoS) of ATM networks. This has been the major driving force for continued interest in the development of variety of ATM switches having their inherent merits for specific applications. Theoretical analysis of maximum and minimum queue length for determination of Available Bit Rate (ABR) and resource management delays is presented followed by computation of queue length, time delay parameters, link utilization ( ρ ) and cell loss probability ( Ploss ) for a given QoS

Switch Modeling

Analogy with Fluid Flow

Analytical Results

Analysis of Network Parameters

Conclusion