2019/01/10 by P.M. Lane, Lane, Phil, Richard Hill +1
Computer Science · #Cloud Computing and Resource Management #Distributed #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #IoT and Edge/Fog Computing #Parallel #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.1901.03054
openalex publication_date 2019/01/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Industrial organisations, particularly Small and Medium-sized Enterprises (SME), face a number of challenges with regard to the adoption of Industrial Internet of Things (IIoT) technologies and methods. The scope of analytics processing that can be performed on data from IIoT-enabled industrial processes is typically limited by the compute and storage resources that are available, and any investment in additional hardware that is sufficiently flexible and scalable is difficult to justify in terms of Return On Investment (ROI). We describe a distributed model of data transport and processing that eases the take-up of IIoT, whilst also enabling a capability to securely deliver more complex analysis and future insight discovery, than would be possible with traditional network architectures.