Performance evaluation of adaptive ABR voice over ATM networks, 2001

Item — Call Number: MU Thesis Obe

Identifier: b2194892

Scope and Contents

From the Collection:

The collection consists of theses written by students enrolled in the Monmouth University graduate Computer Science program. The holdings are primarily bound print documents that were submitted in partial fulfillment of requirements for the Master of Science degree.

Dates

Creation: 2001

Creator

Obeidat, Suhaib A. (Author, Person)
Obaidat, Mohammad S. (Mohammad Salameh), 1952- (Thesis advisor, Person)

Conditions Governing Access

All analog collection holdings are limited to library use only.

Collection holdings may not be borrowed through Interlibrary Loan.

Researchers seeking to photocopy collection materials must complete an Application to Photocopy Form.

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The Monmouth University Library reserves the right to limit or refuse duplication requests subject to the condition of collection materials and/or restrictions imposed by the collection creators or by the United States Copyright Act.

Permission to examine, or copy, collection materials does not imply permission to publish or quote. It is the responsibility of the researcher to obtain such permissions from both the copyright holder and Monmouth University.

Full Extent

1 Items (print book) : 95 pages ; 8.5 x 11.0 inches (28 cm).

Language of Materials

English

Additional Description

Abstract

This work investigates and studies the performance of voice quality when sent over the ABR service in ATM networks. Sources can modify the rate at which they send traffic to the network based on the feedback carried by the Resource Management (RM) cells. This is achieved by changing the encoding level. As the contention increases in the network resources, (bandwith in this case), sources start to reduce the rate at which they generate and send traffic. The efficiency of the scheme under different scheduling/drop policies and other operating conditions and environments has been evaluated using simulation modeling. Furthermore, sensitivity analysis was applied to different parameters (e.g. queue size, averaging interval length) to investigate their effect on the performance metrics. Results show that limiting the number of sources to less than 45% of the link capacity results in an acceptable quality.

Partial Contents

1. Introduction -- 2. Literature review -- 3. The ABR voice model and simulation -- 4. Simulation results and discussion -- 5. Conclusions and recommendations -- 6. References -- Appendix.