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.

中文翻译：

---

工业4.0中基于元胞自动机的MapReduce模型的功能

在这项研究中，基于蜂窝自动机（CA）的具有成本效益的MapReduce模型通过在工业4.0场景中以低能耗促进大数据处理，从而加快了工业信息集成过程。这项研究调查了在几个固定边界条件下基于CA的现有MapReduce设计，以探索其真实动态，并进一步将现有的36条CA规则简化为一组2条CA规则，从而实现了具有成本效益且绿色的MapReduce模型实施在工业4.0中。几种基于相关性的分析可确保MapReduce数据块中的混洗质量。