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Abstract Cellular Automata (CA)-based cost-effective MapReduce model is presented in this research to accelerate the industrial information integration process by facilitating Big Data processing at low energy consumption in Industry… Click to show full abstract
Abstract Cellular Automata (CA)-based cost-effective MapReduce model is presented in this research to accelerate the industrial information integration process by facilitating Big Data processing at low energy consumption in Industry 4.0 scenario. This research investigates an existing CA-based MapReduce design at several fixed boundary conditions to explore its true dynamics and further reduces the existing set of 36 CA rules into a set of 2 CA rules only, towards a cost-effective and Green implementation of MapReduce model in Industry 4.0. Several correlation-based analyses ensure the quality of shuffle in MapReduce data block.
Journal Title: Journal of Industrial Information Integration
Year Published: 2021
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