OBJECTIVES:
To understand the design, implementation and performance of Network proto- cols using the very popular TCP/IP protocol suite as a case study. The students will have hands-on experience on low-level tools and will access and study the source code of these protocols.
TOPICS:
o Program Interface To Protocols.
o IP low level protocols: ARP, RARP and ICMP.
o IP Routing Protocols: RIP and
P.
o UDP protocol.
o Multicasting and IGMP.
o Domain Name Server.
o TCP specification details and performance.
o Ethernet Interface and Driver.
o IP Packet Processing, Fragmentation and Reassembly.
o TCP implementation details in UNIX with reference to source code.
Text Books
Required:
TCP/IP Illustrated, VOLUME 1: The Protocols, By W. Richard Stevens, Ad-
dison Wesley, 1994.
TCP/IP Illustrated, VOLUME 2: The Implementation, By Gary R. Wright and
W. Richard Stevens, Addison Wesley, 1995.
References:
Internetworking with TCP/IP: Principles, Protocols, and Architectures VOL-
UME I, Second Edition, by Douglas Comer, Prentice-Hall, 1991.
Internetworking with TCP/IP: Client-Server Programming and Applications,
By Douglas E. Comer and David L. Stevens, Prentice-Hall, 1993.
UNIX Network Programming, by W. Richard Stevens, Prentice-Hall, 1990.
\subsection{ CS 786/886 Expert Systems }
Objectives:
Expert system approach, advantages and limitations. Knowledge representation
methods, advantages and limitations. Knowledge acquisition. Methods of
inference. Reasoning under uncertainty and inexact reasoning. Tools for
expert system implementation. Applications of expert systems. Project of
expert system implementation.
Prerequisites: CS 480/580.
Textbook:
Joseph Giarratano and Gary Riley
Expert Systems, Principles and Programming
PWS-Kent Publishing, Boston, 1989
References:
Papers in journals and conference proceedings on Artificial Intelligence, Expert Systems, and related topics.
Outline:
\begin{verbatim}
1. Introduction and overview
2. C Language Integrated Production System, CLIPS
3. Meaning and representation of knowledge
4. Resolution systems and deduction
5. Shallow and causal reasoning
6. Analogy, abduction, nonmonotonic reasoning
7. Probability and reasoning
8. Uncertainty and rules
9. Fuzzy systems
10. Expert system life cycle
11. Expert system shells
12. Applications of expert systems
13. Advanced topics