Abstract
The tremendous number of sensors and smart objects deployed in the Internet of Things (IoT) pose a huge potential for the IoT real-time monitoring applications to detect and react to the real world. The insufficient capacity of the IoT data real-time processing has hampered the growth of the IoT real-time monitoring applications. We focus on two issues of the IoT data real-time processing: 1) how to efficiently transform a large number of raw sensing data into meaningful complex event, and 2) how to adapt to the complexity and changeability of monitoring business logic. This paper proposes a universal complex event processing (CEP) mechanism for the IoT real-time monitoring. We propose a formalized hierarchical complex event model including raw event, simple event, and complex event, which reduces the complexity of event modeling. The model supports complex time and space semantics to define flexible complex events by a programming way. Based on this model, we propose a CEP system architecture, in which the system is deployed on the network edge between sensing devices in terminal and applications in the cloud. The complex event definition can be mapped to the CEP rule logic script to detect the potential abnormal event timely. The proposed CEP mechanism is universal and suitable to any heterogeneous sensing devices and CEP engine. We demonstrate the efficacy of the mechanism with two application case studies that highlight our proposed complex event model and evaluate the performance improvement with experiments.
Highlights
With the rapid development of sensors, GPS position sensors, RFID tags and readers, smart objects and other IoT sensing technologies, the IoT real-time monitoring business is growing rapidly in many IoT innovative applications such as smart logistics, smart farm, environmental monitoring, intelligent transportation and smart power grid, etc [1]–[7]
Existing research does not address these challenges well. Focusing on these two problems, this paper proposes a hierarchical event model and a general event processing system architecture to provide a solution for efficient real-time monitoring data processing
Tc increases by 4% compared to 9.5% for time-independent semantics complex event processing
Summary
With the rapid development of sensors, GPS position sensors, RFID tags and readers, smart objects and other IoT sensing technologies, the IoT real-time monitoring business is growing rapidly in many IoT innovative applications such as smart logistics, smart farm, environmental monitoring, intelligent transportation and smart power grid, etc [1]–[7]. How to efficiently transform a large number of raw sensing data into meaningful complex event is a challenge of high computational performance. How to adapt to the complexity and changeability of monitoring business logic of various fields is a challenge of the event refactoring capability These challenges seriously restrict the development of IoT large-scale real-time monitoring applications. Existing research does not address these challenges well Focusing on these two problems, this paper proposes a hierarchical event model and a general event processing system architecture to provide a solution for efficient real-time monitoring data processing. 3) Two application case studies of IoT monitoring for fruit transportation and city road manhole cover status are implemented based on the CEP system to highlight our proposed complex event model.
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