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Parallel MCNN (PMCNN) with application to prototype selection on large and streaming data

Devi V. S., Meena L.

Journal of Artificial Intelligence and Soft Computing Research

2017

Vol. 7, No. 3

155--169

The Modified Condensed Nearest Neighbour (MCNN) algorithm for prototype selection is order-independent, unlike the Condensed Nearest Neighbour (CNN) algorithm. Though MCNN gives better performance, the time requirement is much higher than for CNN. To mitigate this, we propose a distributed approach called Parallel MCNN (pMCNN) which cuts down the time drastically while maintaining good performance. We have proposed two incremental algorithms using MCNN to carry out prototype selection on large and streaming data. The results of these algorithms using MCNN and pMCNN have been compared with an existing algorithm for streaming data.

Efficient Routing In Ad Hoc Network Using Multiple Disjoint Energy Aware Minimum Connected Dominating Sets

Acharya T., Rroy R.

Foundations of Computing and Decision Sciences

2010

Vol. 35, No. 3

145-170

We propose a distributed heuristic algorithm for finding power aware connected dominating set in a graph representing an ad hoc network. Simulation results show that we can route more packets compared to fixed dominating set finding algorithms. An extension of our algorithm constructs multiple node-disjoint power aware minimum connected dominating sets. Applying multi-path routing strategies on this multiple dominating sets, we show that the new algorithm works better than other power aware dominating set based schemes and offers results competitive with general power aware schemes in terms of various energy consumption metrics while maintaining smaller size of the dominating set.

A self-stabilizing algorithm for edge-coloring of graphs

Kuszner Ł., Nadolski A.

Foundations of Computing and Decision Sciences

2006

Vol. 31, No. 2

158-167

Assignment and sequencing of parts to autonomous workstations

Lucertini M., Nicolo F., Smriglio S.

Control and Cybernetics

2000

Vol. 29, no 1

221-236

We present an optimization-based coordination protocol among autonomous workstations in a multiprocessor stage devoted to painting of the shutters in a furniture production process. The coordination aims to maximize the number of parallel operations executable at each machine cycle, while fulfilling constraints on the unique-copy tools. The mechanism is derived by a distributed implementation of a bipartite matching algorithm. The resulting procedure is shown to be compatible with the several autonomous decisions characterizing the process.