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Fog computing-based complex event processing for Internet of Things

Fog computing-based complex event processing for Internet of Things

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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.

Chapter Contents:

  • 8.1 Fog computing
  • 8.1.1 Architecture of fog computing
  • 8.1.2 Related terms
  • 8.1.3 Characteristics of fog computing
  • 8.1.4 Service level objectives
  • 8.1.4.1 Computation management
  • 8.1.4.2 Latency management
  • 8.1.4.3 Resource management
  • 8.1.4.4 Energy management
  • 8.1.4.5 Reliability management
  • 8.1.4.6 Security and privacy management
  • 8.1.4.7 Mobility management
  • 8.1.5 Application areas
  • 8.1.5.1 Health-care systems
  • 8.1.5.2 Smart grid/city environment
  • 8.1.5.3 Vehicular networks/smart traffic lights
  • 8.1.5.4 Augmented reality
  • 8.1.5.5 Pre-caching
  • 8.1.6 Limitations and challenges
  • 8.1.7 Incorporating fog computing with emerging technologies
  • 8.1.7.1 Fifth generation
  • 8.1.7.2 Software-defined networking
  • 8.1.7.3 Network function virtualization
  • 8.1.7.4 Named data networking
  • 8.1.7.5 Content delivery network
  • 8.2 Complex event processing
  • 8.2.1 Basic definitions
  • 8.2.2 CEP reference architecture
  • 8.2.2.1 Design time
  • 8.2.2.2 Run time
  • 8.2.2.3 Administration
  • 8.2.3 Event detection models
  • 8.2.4 Event-processing languages
  • 8.2.4.1 Stream-oriented
  • 8.2.4.2 Rule-oriented
  • 8.2.4.3 Imperative
  • 8.2.5 Algorithms used in CEP
  • 8.2.5.1 Data volume
  • 8.2.5.2 Data continuity
  • 8.2.5.3 Data bound
  • 8.2.5.4 Data evolution
  • 8.2.5.5 Singular classifier approach
  • 8.2.5.6 Ensemble classifier approach
  • 8.2.5.7 Single-pass algorithms
  • 8.2.5.8 Windowing approaches
  • 8.2.6 Application areas
  • 8.2.6.1 Transportation and traffic management
  • 8.2.6.2 Health
  • 8.2.6.3 Smart building
  • 8.2.6.4 Smart grid/smart city
  • 8.2.6.5 Other domains
  • 8.2.7 Complex-event-processing challenges
  • 8.2.8 Trends and future directions in event processing
  • 8.3 An example scenario: smart city
  • 8.4 Conclusion
  • References

Inspec keywords: Internet of Things; smart cities; cloud computing

Other keywords: fog-computing-based IoT solutions; stream data processing techniques; CEP technique; fog computing-based complex event processing; Internet of Things; fog-computation-based distributed architecture; IoT data; layered fog architecture; information extraction

Subjects: Ubiquitous and pervasive computing; Public administration; Internet software

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