Computer Network Design
Types of computer networks: LANs, VLANs, and WANs. Routing algorithms androuting protocols. The network development life cycle. Network analysis and designmethodology. Network design issues: Manageability; Node placement and sizing;Link topology and sizing; Routing; Reliability. Data in support of network design.Structured enterprise network design. Hierarchical tree network design: Terminalassignment; Concentrator location. Mesh topology optimization. Traffic flow analysis.Analysis of loss and delay in networks. Network reliability issues.
Computer and Network Security
Principles and practice of network and internetwork security. Mathematical principlesof cryptography and data security. Conventional and modern crypto systems. Securecommunication protocols. Authentication and Digital Signatures. Secure IP and SSL.Modern applications like digital cash and secure distributed computing. Operationalaspects of computer and network security.
Network Management
Management Protocols. Remote Management. Configuration for Data Collection.Monitoring and Reconfiguration. Operational Issues in Managing HeterogeneousNetworks under Different Operating Systems.
Fault Tolerance and Reliability in Computer Networks
Fundamental concepts in the theory of reliable computer systems design. Hardware andsoftware reliability techniques. Evaluation of fault-tolerant computer communicationsystems. The practices of reliable system design. Case studies. Fault-tolerant topologydesign. Computer networks reliability and fault-toler-ance. Fault tolerant high-speednetworks.
Modeling and Analysis of Computer Networks
Modeling. General concepts. Performance measures. Performance evaluationtechniques. Model Validation. Introduction to Queuing Networks and Stochastic Processes. Simulation. The modeling cycle. Queuing network modeling. Flow analysis.Bottleneck analysis. Hierarchical modeling. Introduction to Analysis driven Design.Case studies with applications to different aspects of computer network systems.
Systems Development Methodologies
Information analysis. Information systems planning. Various approaches to Systems development: Participative, Prototyping, Phenomenological, Evolutionary,etc. Systems development methodologies: Soft systems methodology, information engineering, SSADM, ISAC, etc. Systems development environments.Deliverables. Project management and control.
Information Systems Planning
Concepts of organizational planning. The Planning process. Computational sup-port for planning. Understanding information systems planning: functions, proc-esses, information groups, subject databases. Information systems planning meth-odologies. Information needs analysis. Strategic planning of information sys-
tems. IS planning for competitive advantages. Students should complete an ISplan real life situation of reasonable complexity as a term project.
Formal Derivation of Programs
Predicate calculus. Program semantics of guarded commands. Postconditionsand specifications. Weakest preconditions. Weakest liberal preconditions. Loopinvariants. Termination and non-termination. Partial and total functions. Non-determinacy. Standard techniques in program derivation. Examples of programderivation.
Semantics of Programming Languages
Formal methods for the description of programming languages. Operational,axiomatic and denotational semantics, attribute grammar, two-level grammars.Fixed-point theory of computation. Verification techniques.
Compiler Optimization
Program optimization for speed and size. Reducing redundancy. Register alloca-tion optimization. Data flow analysis and code optimization. Fast optimizationalgorithms. Optimization methods in existing compilers. Optimization problemsfor special languages.
Distributed Operating Systems
Distributed system architectures and distributed processing. Communicationprimitives: remote procedure call and message passing methods. Resource shar-ing. Distributed deadlock management. Naming. Load balancing. Fault toler-ance. File service. Protection issues. Design issues. Projects on important as-pects of distributed and network operating systems. Case studies.
Parallel Computation
Various Parallel Computation Models, such as: PRAM Models, CRCW, CREW, ERCW,EREW. Simulations of PRAM models. Alternation. Boolean Circuits. Parallel Com-putation Thesis. Cellular Automata. Parallel Complexity Measures; NC Class.Simulations of Different Parallel Computation Models.
Reliability and Fault Tolerance of Computer Systems
Reliability and fault-tolerance of computer networks such as FDDI, double loop,hypercube, multi-stage interconnection network, multiprocessor systems, etc.Reliable and fault-tolerant routing, Reliability evaluation algorithms, Availabil-ity and survivability of computer systems, Reliability models of JPL-STAR, FTMP,ESS No. 1, PLURIBUS, etc. Software fault tolerance and reliability. Projects usingnetwork reliability evaluation tools such as SYREL, SHARPE and SPNP.
Computer Systems Performance
Queuing theory. Stochastic Petrinets and Markov Chains. Separable queuing net-works. Priority queuing systems. Evaluation studies: monitoring techniques,modeling methods and model validation. Application of queuing theory to com-puter time-sharing & multi-access systems, multiprocessor systems, intercon-nection networks. Computer communication networks. Case studies of severaldistributed and network system configurations.
Advanced Neural Networks
Introduction to neural computation. Biological neurons. Fundamental conceptsbehind various models of neural networks. Functional equivalence and conver-gence properties of neural network models. Adaptation and learning in neuralnetworks: associative, competitive, inhibitory, and adaptive resonance modelsof learning. Back-propagation, Hopfield Nets, Boltzmann machines, Cauchy ma-chines, ART, and feature map (Kohonen model). Cognitron and neocognitron.VLSI, optical, and software implementations. Potentials and limitations of neu-ral networks. Applications to vision, speech, motor control and others. Projects.
Robotics Programming
Review of issues in robotics programming. In depth study of robotic program-ming languages. Design and implementation of robotic programming languagesand environments. Single and multi-robot environments. Case studies. Project.
Advanced Computer Vision
The physics of vision and its computational modeling. Applications to Robotvision. Image formation and sensing. Basic image processing: edge finding, im-
age segmentation, and texture analysis. Reflectometry: brightness, color andreflectance map. Shape from shading. Photogrammetry and stereo. Motion fieldsand optic flow. Passive navigation and structure from motion. Active vision.Representations, primer sketch, 2.5-D map, 3D map. Human visual system.
Non-Conventional Computer Arithmetic
Mixed base number systems. Negative base arithmetic. Logarithmic based arith-metic. Residue number systems. P-adic numbers. Signed digit arithmetic. Rep-resentation of Complex numbers. Relational number arithmetic. Examples.
Parallel and Vector Architectures
Parallel models of computation. Concept of pipelining at different levels of ar-chitecture. Pipelined functional units. Pipelined vector processors. Vectorizingcompilers and software. Operating system support for vector scheduling andload balancing. Parallel languages. Parallel algorithms. Concurrentization andvectorization.
VLSI Array Processors
Impact of VLSI on computer architecture. Mapping algorithms onto array struc-tures: dependency graphs, signal flow graphs. Design and analysis of systolicarrays. Wave front array processors. Retiming and systolicization. Implementa-tion and verification of array processors. Examples.
Design Issues of VLSI Programmable ASICs
ASIC design methodologies. Programmable ASICS. Field Programmable GateArrays: Architecture, Programming technologies, Design parameters and mod-els. FPGA technology mapping techniques, Routing techniques, Placement tech-niques and Testability.
Silicon Compilation and High-level Synthesis
Levels of abstraction: behavioral, structural, and physical levels. Design de-scription. Module generation (functional cell generation, gate matrix layout,PLAs, etc.) and Module optimization. High level synthesis: Intermediate forms(data flow and control flow graphs), Scheduling algorithms, data flow and con-
trol flow synthesis, resource allocation, and module binding. Knowledge basedand expert system approach to Design Automation.
Advanced Digital System Testing
Fault Modeling. Test Generation. Built-in test and Self-test concepts for hierar-chical circuit models. Complex microprocessors and semiconductor memories.
Independent Study
A specialized topic that may not be broad enough to be offered as a regularcourse. To be arranged with the instructor.
Special Topics in Computer Science
Any state of the art topics or topics of recent interest in any areas in computerscience that may not fit well with the description of the previously mentionedcourses.
Special Topics in Computer Engineering
Any state of the art topics or topics of recent interest in any areas in computerengineering that may not fit well with the description of the previously men-tioned courses.
Seminar
This involves attending the regular departmental seminars, presenting one work in one of the seminars, and producing a final report to the satisfaction of the seminar co-ordinator. This course carries not credit.
Ph.D. Dissertation Work
This is intended to document the effort that would have to be put into theoriginal work conducted by a potential Ph.D. aspirant.