A Real-Time Entity Monitoring based on States and Scenarios

Abstract

Scenario: The current markets require online processing and analysis of data as soon as they arrive to make decisions or implement actions as soon as possible. PAbMM is a real-time processing architecture specialized in measurement projects, where the processing is guided by measurement metadata derived from a measurement framework through the project definition. Objective: To extend the measurement framework incorporating scenarios and entity states as a way to online interpret the indicator’s decision criteria according to scenarios and entity states, approaching their conditional likelihoods. Methodology: An extension based on entity and context states is proposed to implement scenarios and entity states. A memory structure based on the occurrence matrix is defined to approach the associated conditional likelihoods while the data are processed. A new hierarchical complimentary schema is introduced to foster the project definition interoperability considering the new concepts. An extension of the cincamipd library was carried forward to support the complementary schema. An application case is shown as a proof-of-concept. Results: A discrete simulation is introduced for describing the times and sizes associated with the new schema when the volume of the projects to update grow-up. The results of the discrete simulation are very promising, only 0.308 seconds were necessary for updating 1000 active projects. Conclusions: The simulation provides an applicability reference to analyse its convenience according to the project requirements. This allows implementing scenarios and entity states to increase the suitability between indicators and decision criteria according to the current scenario and entity state under analysis.