Data Mining in Cloud-Edge Computing Platforms: Advances and Trends

Dear Colleagues,

With the continuous development of the Internet of Things (IoT), massive amounts of data are generated at the network edges, in which timely and secure processes are critical to the success of IoT applications. In the past decade, data mining (particularly deep learning) has become a hot research topic. Most of the related studies have been conducted on homogeneous cloud servers that contain the same types of machines. However, real IoT applications usually run on heterogeneous edge–edge collaborative platforms, and in recent years, the use of data mining algorithms within such platforms has attracted increasing research interest. Thus, the goal of this Special Issue is to shed light on the progress made in the past few years regarding the development and use of data mining techniques in edge–cloud platforms.

The aim of the current Research Topic is to cover promising, recent, and novel research trends regarding data mining in edge–cloud platforms. Areas to be covered in this Research Topic may include, but are not limited to:

• New paradigms of data mining in edge–cloud platforms;
• Resource management in edge–cloud platforms;
• Designs to enhance data privacy and security in edge–cloud platforms;
• Designs to mine IoT data in edge–cloud platforms;
• Strategies for decentralized data mining at the edge;
• System and algorithm design for data mining incorporating edge and cloud computing;
• Testbed/benchmarks of data mining for edge–cloud platforms.

Dr. Rui Han
Dr. Li Guo
Dr. Xian Yang
Guest Editors

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• data mining
• cloud and edge computing
• edge-cloud collaborative platforms
• deep learning