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Full-Text Articles in Physical Sciences and Mathematics
Multiprocessor Document Allocation: A Neural Network Approach, Abdulaziz Sultan Al-Sehibani, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Multiprocessor Document Allocation: A Neural Network Approach, Abdulaziz Sultan Al-Sehibani, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Electrical Engineering and Computer Science - Technical Reports
We consider the problem of distributing the documents to a given set of processors so that the load on each processor is as equal as possible and the amount of communication is as small as possible. This is an NP-Complete problem. We apply continuous as well as discrete Hopfield neural networks to obtain suboptimal solutions for the problem. These networks perform better than a genetic algorithm for this task proposed by Frieder et al. [4]; in particular, the continuous Hopfield network performs extremely well.
Performance Modeling Of Load Balancing Algorithms Using Neural Networks, Ishfaq Ahmad, Arif Ghafoor, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Performance Modeling Of Load Balancing Algorithms Using Neural Networks, Ishfaq Ahmad, Arif Ghafoor, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
This paper presents a new approach that uses neural networks to predict the performance of a number of dynamic decentralized load balancing strategies. A distributed multicomputer system using any distributed load balancing strategy is represented by a unified analytical queuing model. A large simulation data set is used to train a neural network using the back–propagation learning algorithm based on gradient descent. The performance model using the predicted data from the neural network produces the average response time of various load balancing algorithms under various system parameters. The validation and comparison with simulation data show that the neural network is …