Sensor-Based Edge, Fog, and Cloud Computing: Enabling Next-Generation IoT Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".
Deadline for manuscript submissions: closed (20 March 2025) | Viewed by 3219
Special Issue Editors
Interests: distributed systems; network and information security; IoT security; cyber security; machine learning and deep learning
Interests: THz/RF sensing; radar technology; advanced signal processing; antennas and propagation; healthcare technology
Special Issues, Collections and Topics in MDPI journals
Interests: IoT; WSN; robotics and embedded hardware/software to industry; smart cities; agricultural environments
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid growth of Internet of Things (IoT) applications has led to an exponential increase in the volume of sensor-generated data. Traditional centralised cloud computing architectures struggle to handle the massive influx of data, leading to latency issues, bandwidth constraints, and increased costs. To address these challenges, a distributed computing paradigm has emerged, combining edge, fog, and cloud computing.
Edge computing brings computation and data storage closer to the data source, reducing latency and bandwidth requirements. Fog computing extends this concept by introducing intermediate computing nodes between the edge and the cloud, enabling localised data processing and analytics. Cloud computing, on the other hand, offers vast storage and computing resources for scalable and elastic data processing.
The integration of sensor-based edge, fog, and cloud computing offers a promising solution to overcome the limitations of centralised cloud architectures. It enables real-time data processing, efficient resource utilisation, and improved scalability for IoT applications. By leveraging the strengths of each computing layer, this integration enables a wide range of applications, including smart cities, industrial automation, healthcare monitoring, environmental monitoring, and more.
However, the integration of these computing paradigms also poses several challenges. These include data management and synchronisation, security and privacy concerns, resource allocation and optimisation, and the design of efficient algorithms for distributed data processing. This Special Issue aims to address these challenges and explore the advancements in sensor-based edge, fog, and cloud computing to enable next-generation IoT applications.
This Special Issue therefore aims to collect original research and review articles on recent advances, technologies, solutions, applications, and new challenges in the field of sensor-based edge, fog, and cloud computing systems.
- Sensor data acquisition, processing, and analysis at the edge, fog, and cloud layers.
- Edge computing architectures and algorithms for real-time sensor data processing.
- Fog computing frameworks for distributed sensor data analytics.
- Cloud-based sensor data storage, retrieval, and processing.
- Integration of edge, fog, and cloud computing for scalable and efficient IoT applications.
- Security and privacy challenges in sensor-based edge, fog, and cloud computing.
- Machine/deep learning for security in sensor-based edge, fog, and cloud computing.
- AI-based data analytics in sensor-based edge, fog, and cloud computing.
- Case studies and real-world deployments of sensor-based edge, fog, and cloud computing.
- Performance evaluation and benchmarking of sensor-based edge, fog, and cloud computing.
Dr. Amna Eleyan
Dr. Syed Aziz Shah
Dr. Umar Raza
Guest Editors
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Keywords
- sensors
- edge computing
- fog computing
- cloud computing
- Internet of Things (IoT)
- real-time processing
- data fusion and analytics
- security and privacy
- machine learning and deep learning
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