Cloud/Edge/Fog Computing and Blockchain Technologies for Artificial Intelligence of Things

Dear Colleagues,

According to the Internet of Everything paradigm, all things should be connected. The idea of the Internet of Things (IoT) developed as a comprehensive proposal to allow communication and interaction amongst an ecosystem of various, heterogeneous networked items and devices. Understanding the electronic parts, communication protocols, real-time analytic methods, and the locations of the items and devices is important to make the IoT ecosystem a reality.

IoT and artificial intelligence (AI) should work together harmoniously. Machine learning (ML) techniques boost the potential of the IoT and the ability to make decisions based on the data provided by devices. The IoT can create the volume of data required to feed ML models. Edge, fog, and cloud are the three layers that make up an IoT architecture. Although cloud computing has historically favored ML algorithms because of its superior computational performance, ML may be used across all IoT tiers. IoT devices can now conduct more complicated computational processes as a result of their rapid evolution. The development of more sophisticated analysis algorithms in the edge computing layer has been made possible by this fact. Consequently, the idea of the “Artificial Intelligence of Things” (AIoT) has emerged.

The AIoT may benefit from the use of blockchain in IoT. With the purpose of identifying the devices and ensuring a secure, scalable, transparent, and traceable network, it might be the ideal ally to establish an IoT ecosystem. To learn, infer, and reach conclusions, machine learning algorithms rely on data or information. Blockchains function as a distributed ledger where information may be kept and exchanged in a fashion that is cryptographically signed, verified, and accepted by all mining nodes. Blockchain data are securely kept and untouchable because of the great integrity and resilience of the system. When used with ML models, the smart contract concept can provide more security and dependability than the inference stage.

Some topics of interest include, but are not limited to:

• IoT applications taking advantage of edge/fog/cloud distributed computing;
• Distributed architectures in support of IoT applications;
• Trust data collection and computing for distributed IoT using AIoT;
• Machine learning and data science in/for edge–fog–cloud IoT;
• Edge/fog-computing-based algorithms/method design for edge–blockchain systems;
• The role of blockchain in the convergence of AI, IoT, and edge–cloud;
• Implementation/testbed/deployment of edge/fog/cloud computing, AIoT and blockchain.

Dr. Sergio Trilles Oliver
Guest Editor

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• edge computing
• fog computing
• cloud computing for Internet of Things
• artificial Internet of Things
• blockchain