Fog computing-based complex event processing for Internet of Things

Abstract

This chapter addresses data collection and real-time analysis of massive IoT data using a horizontally distributed fog -computing architecture. We explain how data -analysis problem of IoT can be handled in a layered fog architecture so that information extraction can be achieved in both local and global scales. We provide a deep investigation of existing fog-computing-based IoT solutions in a categorical manner and discuss the open-research problems. In terms of big data analysis, stream data mining and CEP techniques are proven to be quite promising solutions in the literature. Currently, stream data processing tools and techniques are mainly developed for cloud -based systems. However, there is an urgent need for adapting these techniques to horizontally distribute IoT-based data collection and analysis systems. We perform an extensive survey on stream data processing techniques by focusing on their ability to work on fog-computing -based IoT systems. We document a significant survey of CEP techniques in IoT systems by providing pros and cons of each scheme. An example scenario was also provided to show that the problem of collection and real-time analysis of massive IoT data can be solved using fog-computation-based distributed architecture and CEP techniques.