Ajay K. Katangur

A Novel Multistage Network Architecture with Multicast and Broadcast Capability

In this paper, a new class of optical multistage interconnection network (MIN) architecture is presented, which is constructed utilizing a modularization approach rather than the traditional recursive or fixed exchange pattern methods. The modified architecture consists of an input module, an output module, two point-to-point (PTP) modules, and one modified multicast/broadcast (M/B) module(s). We also implement the multicast/broadcast module with WDM technique, which reduces the hardware cost required for multicast and the re-computation cost for a new connection. We show that it has the best application flexibility and provides multicast function without imposing significant negative impacts on the whole network. A new multicast connection pattern is also proposed in this paper, which makes it practical and economical to apply amplification in space-division networks. Compared with existing multicast architectures, this new architecture with Dilated Benes PTP modules has better performance in terms of system SNR, the number of switch elements, and system attenuation in point-to-point connections. Moreover, the multicast/broadcast module adopts wavelength division multiplexing (WDM) technique to increase its multicast/broadcast assignment. As a result, given m available distinguished wavelengths, one M/B module can support at most m M/B requests at the same time. The new proposed M/B module with WDM is more practical and economical to apply amplification in space-division networks.

Message routing and scheduling in optical multistage networks using simulated annealing

Multistage Interconnection Networks (MIN) is popular in switching and communication applications. A major problem called Cross talk is introduced by optical MIN, which is caused by coupling two signals within a switching element. In this paper, we focus on an efficient solution to avoid cross talk, which is routing traffic through an N × N optical network to avoid coupling two signals within each switching element. Under the constraint of avoiding cross talk, what we are interested is how to realize a permutation that will use the minimum number of passes. This routing problem is an NP-hard problem. Many heuristic algorithms are designed by many researchers to perform this routing such as sequential algorithm, degree-descending algorithm, etc. The Simulated Annealing algorithm is used in this research to improve the performance of solving the problem and optimizing the result. Many cases are tested and the results are compared to the results of other algorithms to show the advantages of good quality solution and short execution time of Simulated Annealing algorithm.

Simulated annealing routing and wavelength lower bound estimation on wavelength-division multiplexing optical multistage networks

Multistage interconnection networks (MINs) are popular in switching and communication applications and have been used in tele- communication and parallel computing systems for many years. Crosstalk a major problem introduced by an optical MIN, is caused by coupling two signals within a switching element. We focus on an efficient solution to avoiding crosstalk by routing traffic through anN3N optical network to avoid coupling two signals within each switching element us- ing wavelength-division multiplexing (WDM) and a time-division ap- proach. Under the constraint of avoiding crosstalk, the interest is on realizing a permutation that uses the minimum number of passes for routing. This routing problem is an NP-hard problem. Many heuristic al- gorithms are already designed by researchers to perform this routing such as a sequential algorithm, a degree-descending algorithm, etc. The genetic algorithm is used successfully to improve the performance over the heuristic algorithms. The drawback of the genetic algorithm is its long running times. We use the simulated annealing algorithm to improve the performance of solving the problem and optimizing the result. In addition, a wavelength lower bound estimate on the minimum number of passes required is calculated and compared to the results obtained using heu- ristic, genetic, and simulated annealing algorithms. Many cases are tested and the results are compared to the results of other algorithms to show the advantages of simulated annealing algorithm.

Protein secondary structure prediction using neural network and simulated annealing algorithm

Predicting the secondary structure of a protein (alpha-helix, beta-sheet, coil) is an important step towards elucidating its three dimensional structure, as well as its function. In this research we use a multilayer feed forward neural network for protein secondary structure prediction. The RS126 data set was used for training and testing the proposed neural network. We combined neural network and simulated annealing (SA) to further improve on the accuracy of protein secondary structure prediction. The results obtained show that by combining the neural network with SA technique improves the prediction accuracy in the range of 2-3%.

Novel modularized optical multistage interconnection network architecture with multicast capability

Summary form only given. In this paper, a new class of optical multistage interconnection network (MIN) architecture is presented, which is constructed utilizing a modularization approach rather than the traditional recursive or fixed exchange pattern methods. We show that it has the best application flexibility and provides multicast function without imposing significant negative impacts to the whole network. A new multicast pattern is also proposed here, which makes it practical and economical to apply amplification in space-division networks. Compared with existing multicast architectures, this new architecture with Dilated Benes PTP modules has better performance in terms of system SNR, the number of switch elements, and system attenuation in point-to-point connections.

Protein Secondary Structure Prediction using Bayesian Inference method on Decision fusion algorithms

Prediction of protein secondary structure (alpha-helix, beta-sheet, coil) from primary sequence of amino acids is a very challenging task, and the problem has been approached from several angles. Previously research was performed in this field using several techniques such as neural networks, simulated annealing (SA) and genetic algorithms (GA) for improving the protein secondary structure prediction accuracy. Decision fusion methods such as the committee method and correlation methods were also used in combination with the profile-based neural networks and AI algorithms for achieving better prediction accuracy. In this research we investigate the Bayesian inference method for predicting the protein secondary structure. The Bayesian inference method proposed in this research uses the results from the committee and correlation methods to achieve better prediction accuracy. Simulations are performed using the RS126 data set. The results show that the protein secondary structure prediction accuracy can be improved by more than 2% using the Bayesian inference method.

Message Routing and Scheduling in Optical Multistage Networks using Bayesian Inference method on AI algorithms

Optical multistage interconnection networks (MINs) suffer from optical-loss during switching and crosstalk problem in the switches. The crosstalk problem is solved by routing messages using time division multiplexing (TDM) approach. This paper focuses on minimizing the number of groups (time slots) required to realize a permutation. Many researchers concentrated on this NP-hard problem and concluded that AI algorithms perform better than the heuristic algorithms. They also showed that majority of the times the performance of genetic algorithm (GA) was better than simulated annealing algorithm (SAA). In this research, we implement a new approach to minimize the number of passes required for scheduling a given permutation. A combinational method is developed which comprises the use of Bayesian inference method on GA and SAA to always guarantee the best solution, instead of only using either GA or SAA. Simulations are performed in Java using multiple threads to run SA and GAA in parallel and to evaluate the performance of the new method. The results are then compared to those obtained from GA and SAA.

Performance analysis of optical multistage interconnection networks with limited crosstalk

Analytical modeling techniques can be used to study the performance of optical multistage interconnection network (OMIN) effectively. MINs have assumed importance in recent times, because of their cost-effectiveness. An N/spl times/N MIN consists of a mapping from N processors to N memories, with log/sub 2/N stages of 2/spl times/2 switches with N/2 switches per stage. The interest is on the study of the performance of unbuffered optical multistage interconnection network using the Banyan network. The uniform reference model approach is assumed for the purpose of analysis. In this paper we apply the analytical modeling approach on an N/spl times/N OMIN with limited crosstalk (conflicts between messages) unto (log/sub 2/N-1). Messages with switch conflicts satisfying the constraint of (log/sub 2/N-1) are allowed to pass in the same group, but in case of a link conflict, than that message is routed in a different group. The analysis is performed by calculating the bandwidth of the network operating under a load l and allowing random traffic and using a greedy routing strategy. A number of equations are derived using the theory of probability and the performance curves are plotted. The results obtained show that the performance of the network improves by allowing limited crosstalk in the network.