Fog Computing for Spatial Data Infrastructure: Challenges and Opportunities

Fog Computing for Spatial Data Infrastructure: Challenges and Opportunities

DOI: 10.4018/978-1-6684-4466-5.ch008
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Abstract

Fog computing is a promising approach to address the challenges faced by traditional spatial data infrastructure when processing large-scale and real-time data. This chapter examined the opportunities and challenges of using fog computing in SDI through the service dominant logic framework. The study showed that fog computing can improve SDI by providing real-time data processing, improved data security and privacy, and increased accessibility of geospatial data. However, challenges such as data quality and interoperability, collaboration, technical infrastructure, and governance policies need to be addressed. The chapter suggested ways to improve the value co-creation process between fog computing and SDI users, including collaboration and partnership, investment in technical infrastructure, and capacity building initiatives. Future research can investigate the practical implementation and evaluation of fog computing in SDI applications.
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2. Theoretical Background

This section presents a detailed description of two fundamental concepts: fog computing and spatial data infrastructure to provide a comprehensive comprehension of the research topic. The basic definitions, characteristics, and architecture will be covered in the discussion, along with the applications in many fields.

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