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Optimizing Integrated Spatial Data Management Through Fog Computing: A Comprehensive Overview
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Author(s): Munir Ahmad (Survey of Pakistan, Pakistan), Asmat Ali (Survey of Pakistan, Pakistan), Hassan Nawaz (Huawei MiddleEast Cloud, Pakistan), Muhammad Arslan (Chenab College of Advance Studies, Faisalabad, Pakistan)and Nirmalendu Kumar (Survey of India, India)
Copyright: 2024
Pages: 21
Source title:
Digital Technologies in Modeling and Management: Insights in Education and Industry
Source Author(s)/Editor(s): G. S. Prakasha (Christ University, India), Maria Lapina (North-Caucasus Federal University, Russia), Deepanraj Balakrishnan (Prince Mohammad Bin Fahd University, Saudi Arabia)and Mohammad Sajid (Aligarh Muslim University, India)
DOI: 10.4018/978-1-6684-9576-6.ch013
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Abstract
Fog computing offers key features such as real-time communication, physical distribution, position awareness, compatibility, scalability, and energy efficiency, which collectively enhance the management of integrated spatial data. It provides benefits such as real-time data processing, seamless data sharing, improved efficiency, enhanced data security and privacy, and effective resource utilization. The distributed architecture and edge processing capabilities of fog computing enable real-time spatial data processing, faster insights, and localized decision-making. It presents opportunities for web-based analytics, real-time analysis, fault tolerance, event-triggered actions, and context-aware applications. However, challenges exist in terms of user needs and requirements, collaboration and partnership, data quality and interoperability, technical infrastructure, and policy and governance. Future work should focus on addressing these challenges and exploring new opportunities.
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