Abstract
In real-time health analytics, smart cities, military sensing systems, and others, big data analytics is enabled by the introduction of appropriate sensing and actuation systems. The introduction of next generation of sensing and actuation systems or the Internet of Things era has been facilitated by affordable low-power 32-bit microcontrollers combined with low-cost and effective sensors with appropriate power supplies, mobile and local data collection (local big data) capabilities, adaptive behavior using machine learning and evolving model-based behavior, etc. While Cloud computing offers big data processing and actuation capability at the server level, mist computing offers data processing and actuation capability at the very edge of the network. Fog computing offers the same capability in the middle at edge gateways. Mist computing is an enabler for many applications, which cannot be realized with alternative methods, such as smart cities, where city streets adapt to the changes happening in the city, socially intelligent houses where indoor environment management is integrated with inhabitants health monitoring, or military sensing systems where situational information is automatically deduced from raw data and delivered to the information consumers. While these visionary applications promise to change our environment and the way we interact with the environment, we face serious challenges in implementing these systems, such as reliability of data exchange between nodes and routers, power distribution, quality of decision-making, etc.
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Tammemäe, K., Jantsch, A., Kuusik, A., Preden, JS., Õunapuu, E. (2018). Self-Aware Fog Computing in Private and Secure Spheres. In: Rahmani, A., Liljeberg, P., Preden, JS., Jantsch, A. (eds) Fog Computing in the Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-319-57639-8_5
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