Storage Method for Real-Time Big Data on the Internet of Things
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Internet of Things (IoT)".
Deadline for manuscript submissions: 15 March 2025 | Viewed by 9036
Special Issue Editors
Interests: storage systems; database systems; next-generation data infrastructure; new storage techniques
Special Issue Information
Dear Colleagues,
We invite original and unpublished submissions discussing your research to the Special Issue on "Storage Methods for Real-Time Big Data on Internet of Things", with a focus on storage systems, databases, data processing systems, and data platforms for data in IoT.
A large volume of data is generated from the devices and sensors from Internet-of-Things (IoT) systems, which have rapidly evolved and are transforming the way we live, work, and interact with our environments. How to efficiently process, store, and manage such a large volume of real-time data is challenging but has not been well studied. The increasing amount of data generated by IoT devices requires scalable and reliable storage solutions that can handle the volume, velocity, and variety of data. At the same time, the real-time nature of IoT data requires low latency, high performance, and good cost effectiveness to enable quick decision making, data processing, data mining, and AI support.
This Special Issue aims to gather contributions to IoT data storage from both academia and industry. Thereby, the Special Issue will advance with novel approaches, solid system designs and evaluations, creative data processing with AI/ML, novel attacks or state-of-the-art surveys related to the data persistency, protection, processing, and management for real-time big data in IoT. Research areas covered by the Special Issue may include (but are not restricted to) the following:
- File systems
- Cloud storage systems
- NoSQL databases for big data
- Timeseries databases
- Edge computing and data processing
- Embedded storage engines
- Data transmission and caching for IoT
- Real-time data processing
- In-storage, in-network, and in-memory processing
- Data structure and indexing for big data in IoT
- Data security and privacy in IoT
- IoT data-related workload characterization and modeling
- Distributed storage and processing systems for IoT data
- Efficient data storage and process method design
- IoT data analysis, modeling, and measurement
- Distributed AI for data storage and processing
- Joint IoT data transmission and storage optimization
- Experimental testbeds for distributed storage systems
- Privacy and security issues for distributed storage systems
- Data storage in emerging applications, such as autonomous vehicle systems and virtual reality systems
We look forward to receiving your contributions.
Dr. Zhichao Cao
Dr. Mingzhe Chen
Guest Editors
Manuscript Submission Information
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