• Protein structure prediction
• Motif finding
• Clustering techniques in bioinformatics
• Sequence alignment and comparison
• Applying AI techniques such as Genetic
Algorithm, Simulated Annealing, Neural
Network, Support Vector Machine, etc
Simulation of Optical Multistage
• Different Routing Algorithms
• Different Topologies
• Different Traffic (Poisson, self-similar)
• Graphical User Interface (Java)
• Animation (Java)
• Distributed Simulation (RMI in Java)
• Rearrangeable Non-blocking Networks
example: Benes network
• Can realize any permutation, but all the
connection requests have to be known in
• If not known in advance, existing paths
have to rearranged if a conflict arises.
• Never have any conflicts even if connection
requests are not known in advance.
• Crossbar is an example.
• Suitable for optical networks.
• Hardware is costly (O(N^2) hardware).
• Can we find a better network with hardware
cost of O(N log N)?
• What kind of subsets are strictly
• What is the minimum number of
rearrangements if conflicts arise in a
rearrangeable non-blocking networks?
• Simulation using general language (Java or
• Simulate networks using OPNET package
• Design and analysis of routing algorithms
• Design new networks for better
performance (fewer crosstalks, short
distance, fewer conversions, rearrange
• Use neural networks to route messages
• Use genetic algorithms to schedule
• Use simulated annealing to route messages
• Use rule-based systems to do traffic control
• Management software
Database Management for PCS
• Personal Communication Service (PCS)
• Mobile Communication
• Location Management –Home Location
Register (HLR) and Visitor Location
• How to track a Mobile Terminal (MT)?
• Procedure for location registration
• New dynamic database management
• Performance – Analytical and Simulation
• Simulation Program
• Efficient routing algorithms
• Find domination set (graph problem)
• Channel Assignment Problem
• Frequency Reuse
• Fixed Channel Assignment
• Dynamic Channel Assignment
• Greedy Algorithms
• Genetic Algorithms
• Solve engineering problems using MPI,
PVM or OpenMP.
• Implement some CS problems (simulation,
database, sequence alignment algorithms,
data mining or neural networks) using
• Modeling and analysis of parallel task