An evaluation of best effort traffic management of server and agent based active network management (SAAM) architecture

Loading...
Thumbnail Image
Authors
Ayvat, Birol
Subjects
Advisors
Xie, Geoffrey
Date of Issue
2003-03
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
The Server and Agent-based Active Network Management (SAAM) architecture was initially designed to work with the next generation Internet where increasingly sophisticated applications will require QoS guarantees. Although such QoS traffic is growing in volume, Best Effort traffic, which does not require QoS guarantees, needs to be supported for foreseeable future. Thus, SAAM must handle Best Effort traffic as well as QoS traffic. A Best Effort traffic management algorithm was developed for SAAM recently to take advantage of the abilities of the SAAM server. However, this algorithm has not been evaluated quantitatively. This thesis conducts experiments to compare the performance of the Best Effort traffic management scheme of the SAAM architecture against the well known MPLS Adaptive Traffic Engineering (MATE) Algorithm. A couple of realistic network topologies were used. The results show while SAAM may not perform as well as MATE with a fixed set of paths, using SAAM's dynamic path deployment functionality allows the load to be distributed across more parts of the network, thus achieving better performance than MATE. Much of the effort was spent on implementing the MATE algorithm in SAAM. Some modifications were also made to the SAAM code based on the experimental results to increase the performance of SAAM's Best Effort solution.
Type
Thesis
Description
Series/Report No
Department
Computer Science
Organization
Identifiers
NPS Report Number
Sponsors
Funding
Format
xii, 91 p. : ill. (some col.) ;
Citation
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
Collections