Rsps coords list 64411/18/2023 ![]() We show that Streaming MASSIF is able to handle high velocity streams up to hundreds of events per second, in combination with expressive reasoning and complex event processing. Streaming MASSIF is a layered approach allowing IoT service to subscribe to high-level and temporal dependent concepts in volatile data streams. Cascading Reasoning is a vision that has not been fully realized. Each layer minimizes the processed data and increases the complexity of the data processing. Cascading Reasoning is a vision that solves the problem of expressive reasoning over high frequency streams by introducing a hierarchical approach consisting of multiple layers. Therefore, we introduce Streaming MASSIF, a Cascading Reasoning approach performing expressive reasoning and complex event processing over high velocity streams. There is still a mismatch between the complexity of processing and the rate data is produced in volatile domains. ![]() However, current approaches cannot perform the required reasoning expressivity while detecting time dependencies over high frequency data streams. To perform meaningful analysis over multiple of these streams, stream processing needs to support expressive reasoning capabilities to infer implicit facts and temporal reasoning to capture temporal dependencies. ![]() In the Internet of Things (IoT), multiple sensors and devices are generating heterogeneous streams of data.
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