Title page for ETD etd-11197-12405

Type of Document Dissertation
Author Brande, Julia K. Jr.
Author's Email Address Julia_Earp@ncsu.edu
URN etd-11197-12405
Title Computer Network Routing with a Fuzzy Neural Network
Degree PhD
Department Management Science and Information Technology
Advisory Committee
Advisor Name Title
Clayton, Edward R.
Moore, Laurence J.
Rees, Loren Paul
Sumichrast, Robert T.
Rakes, Terry R. Committee Chair
  • Network Routing
  • Fuzzy Reasoning
  • Neural Networks
  • Wide Area Networks
Date of Defense 1997-11-07
Availability unrestricted
The growing usage of computer networks is requiring improvements in network technologies

and management techniques so users will receive high quality service. As more individuals

transmit data through a computer network, the quality of service received by the users begins

to degrade. A major aspect of computer networks that is vital to quality of service is data

routing. A more effective method for routing data through a computer network can assist with

the new problems being encountered with today's growing networks.

Effective routing algorithms use various techniques to determine the most appropriate route

for transmitting data. Determining the best route through a wide area network (WAN),

requires the routing algorithm to obtain information concerning all of the nodes, links, and

devices present on the network. The most relevant routing information involves various

measures that are often obtained in an imprecise or inaccurate manner, thus suggesting that

fuzzy reasoning is a natural method to employ in an improved routing scheme. The neural

network is deemed as a suitable accompaniment because it maintains the ability to learn in

dynamic situations. Once the neural network is initially designed, any alterations in the

computer routing environment can easily be learned by this adaptive artificial intelligence

method. The capability to learn and adapt is essential in today's rapidly growing and

changing computer networks. These techniques, fuzzy reasoning and neural networks, when

combined together provide a very effective routing algorithm for computer networks.

Computer simulation is employed to prove the new fuzzy routing algorithm outperforms the

Shortest Path First (SPF) algorithm in most computer network situations. The benefits

increase as the computer network migrates from a stable network to a more variable one. The

advantages of applying this fuzzy routing algorithm are apparent when considering the

dynamic nature of modern computer networks.

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