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

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Automation Control Theory Perspectives in Intelligent Systems (CSOC 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 466))

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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.

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Correspondence to Belkebir Djalila or Boutekkouk Fateh .

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© 2016 Springer International Publishing Switzerland

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Djalila, B., Fateh, B. (2016). Quantum Evolutionary Cellular Automata Mapping Optimization Technique Targeting Regular Network on Chip. In: Silhavy, R., Senkerik, R., Oplatkova, Z.K., Silhavy, P., Prokopova, Z. (eds) Automation Control Theory Perspectives in Intelligent Systems. CSOC 2016. Advances in Intelligent Systems and Computing, vol 466. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33387-8

  • Online ISBN: 978-3-319-33389-2

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