Edge–Cloud Computing for the Internet of Things: Embedding Intelligence in the Edge with Artificial Intelligence
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 3646
Special Issue Editors
Interests: edge computing; blockchain; deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: ubiquitous computing; edge computing; self-organizing systems; adaptation; Internet of Things; distributed systems
Special Issue Information
Dear Colleagues,
Recently, the term ‘Internet of Things’ (IoT) has elicited escalating attention as an emerging paradigm to satisfy the requirements of agility, flexibility, and ubiquitous accessibility. One of the radical shifts that the IoT has introduced is the ability to sense data from nearby surroundings and carry out self-executing functions. More specifically, its agility, flexibility, and ubiquitous accessibility have encouraged cooperation between artificial learning, edge–cloud computing, and the IoT, referred to as edge intelligence. This pushes learning intelligence from a remote learning center to the network edges. Essentially, physical proximity between data generation sources, users, and learning agents promises a number of high QoS supplements, such as mild bandwidth, energy efficiency, time effectiveness, privacy protection, and on-premises activity. Although edge intelligence has been widely researched to solve the present problems, numerous handicaps prevent it from being used as a generic platform.
This Special Issue invites research on novel functionalities and technologies (including protocols) in edge–cloud computing, IoT, edge intelligence, and artificial intelligence, with respect to several perspectives, including amalgamated algorithms, allocation schemes, incentive modeling and optimization, etc. The issue will provide tutorial information, disseminate recent results, review economic opportunities, examine technical challenges, discuss possible paths to regulatory solutions, and identify future trends.
Dr. Chao Qiu
Prof. Dr. Christian Becker
Guest Editors
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Keywords
- theoretical modeling and performance analysis for edge computing in the IoT
- edge intelligence using crowd-funded computing and networking resource
- adaptability edge computing services for users’ AI insight
- effect of blockchain in edge intelligence and how it helps the IoT
- security, trust, privacy, and identity in edge intelligence helped by the IoT
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