Simultaneous Data Management in Sensor-Based Systems using Metadata, Disaggregation and Processing

High performance sensor-based systems require distributed methods that quickly release threads and allow hardware to scale as the amount of data increases. Each sensor, component, has to handle a massive amount of data, independently, at the same time it must cooperate with other sensors, components. To facilitate rapid data processing between different components and handle the dataflow simultaneously, knowledge about the components, i.e., metadata, can be incorporated. This paper presents a sensor-based system that applies metadata on internal components and utilizes disaggregation and processing as core services to handle large amount of data from various distributed sensors. By combining components with individual advantages, the system can be designed to allow a high amount of simultaneous data to be disaggregated into the respective categories, which are processed to make information accessible and stored in a database that can easily be accessed by interested parties. To evaluate the system, performance tests have been carried out using metadata on combined components, disaggregation and processing. The tests show that it is possible to build faster and more reliable sensor-based systems that are scalable, fault tolerant and high performing.