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Quantum Evolutionary Cellular Automata Mapping Optimization Technique Targeting Regular Network on Chip

  • Belkebir DjalilaEmail author
  • Boutekkouk FatehEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 466)

Abstract

This paper presents a novel method for solving the mapping and scheduling problems in network on chip based on quantum evolutionary cellular automata (QECA). The method applies QECA to handle the multimedia application IP placement and scheduling problem. The QECA method is based on the concept and principles of quantum computing, such as quantum bits, quantum gates and superposition of states. Thus, the mechanism of the QECA method can inherently treat the balance between exploration and exploitation where each Q-bit individual can represent and explore all possible states and drive it to exploit a single state. The use of quantum bit representation leads to better population diversity compared with the classical bit representations while the use of quantum gate drive the population towards the best solution. The achieved results are about 0.99 % of the fitness function over 110 generations.

Keywords

Quantum genetic algorithm Cellular automata Network on chip Quantum computing Energy consumption 

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Copyright information

© Springer International Publishing Switzerland 2016

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 2.5 International License (http://creativecommons.org/licenses/by-nc/2.5/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Authors and Affiliations

  1. 1.Research Laboratory on Computer Science’s Complex System (RELA(CS)2)Oum El-Bouaghi UniversityOum El-BouaghiAlgeria

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