Ontology-Based Integrated Monitoring of Hadoop Clusters in Industrial Environments with OPC UA and RESTful Web Services
作者： Kamil Folkert , Marcin Fojcik
DOI: 10.1007/978-3-319-19419-6_15
关键词: OPC Unified Architecture 、 Computer science 、 Standardization 、 Web service 、 Data science 、 Predictive maintenance 、 Ontology (information science) 、 Big data 、 Predictive analytics 、 Process (engineering)
摘要: Contemporary industrial and production systems produce huge amounts of data in various models, used for process monitoring, predictive maintenance the machines, historical analysis statistics, more. Apache Hadoop brings a cost-effective opportunity Big Data analysis, including generated industries. Integrating into environments creates new possibilities, as well many challenges. The authors this paper are involved commercial scientific projects utilizing industry analytics platform. In such initiatives lack standardization monitoring terms cluster utilization is especially perplexing. paper, propose methodology environments, based on dedicated ontology widely adopted standards: OPC Unified Architecture RESTful Web Services.
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