The development of Industrial Internet of Things (IIoT) and Industry 4.0 has completely changed the traditional manufacturing industry. Intelligent IIoT technology usually involves a large number of intensive computing tasks.
Xiaoheng Deng+5 more
semanticscholar +1 more source
Joint Optimization of Computing Offloading and Service Caching in Edge Computing-Based Smart Grid
IEEE Transactions on Cloud Computing, 2023With the continuous expansion of the power Internet of Things (IoT) and the rapid increase in the number of Smart Devices (SDs), the data generated by SDs has exponentially increased. The traditional cloud-based smart grid cannot meet the low latency and
Huan Zhou+3 more
semanticscholar +1 more source
Task Partitioning and Offloading in DNN-Task Enabled Mobile Edge Computing Networks
IEEE Transactions on Mobile Computing, 2023Deep neural network (DNN)-task enabled mobile edge computing (MEC) is gaining ubiquity due to outstanding performance of artificial intelligence. By virtue of characteristics of DNN, this paper develops a joint design of task partitioning and offloading ...
Mingjin Gao+5 more
semanticscholar +1 more source
AI-Enabled Secure Microservices in Edge Computing: Opportunities and Challenges
IEEE Transactions on Services Computing, 2023The paradigm of edge computing has formed an innovative scope within the domain of the Internet of Things (IoT) through expanding the services of the cloud to the network edge to design distributed architectures and securely enhance decision-making ...
Firas Al-Doghman+4 more
semanticscholar +1 more source
Joint Task Offloading and Resource Allocation for Energy-Constrained Mobile Edge Computing
IEEE Transactions on Mobile Computing, 2023We consider the problem of task offloading and resource allocation in mobile edge computing (MEC). To maintain satisfactory quality of experience (QoE) of end-users, mobile devices (MDs) may offload their tasks to edge servers based on the allocated ...
Hongbo Jiang+3 more
semanticscholar +1 more source
Edge Computing Driven Low-Light Image Dynamic Enhancement for Object Detection
IEEE Transactions on Network Science and Engineering, 2023With fast increase in volume of mobile multimedia data, how to apply powerful deep learning methods to process data with real-time response becomes a major issue.
Yirui Wu+5 more
semanticscholar +1 more source
Accelerating Decentralized Federated Learning in Heterogeneous Edge Computing
IEEE Transactions on Mobile Computing, 2023In edge computing (EC), federated learning (FL) enables massive devices to collaboratively train AI models without exposing local data. In order to avoid the possible bottleneck of the parameter server (PS) architecture, we concentrate on the ...
Lun Wang+4 more
semanticscholar +1 more source
Schema Design with Intelligent Multi Modelling Edge Computing Techniques for Industrial Applications
2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN), 2023The Internet has become one of the most essential sources of information and knowledge for consumers. It is important to figure out how to get users' specific needs from the large number of network document resources in a precise and efficient way ...
P. William+5 more
semanticscholar +1 more source
Wireless Powered Mobile Edge Computing Networks: A Survey
ACM Computing Surveys, 2023Wireless Powered Mobile Edge Computing (WPMEC) is an integration of Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) technologies, to both improve computing capabilities of mobile devices and energy compensation for their limited battery ...
Xiaojie Wang+6 more
semanticscholar +1 more source
Reverse Auction-Based Computation Offloading and Resource Allocation in Mobile Cloud-Edge Computing
IEEE Transactions on Mobile Computing, 2023This article proposes a novel Reverse Auction-based Computation Offloading and Resource Allocation Mechanism, named RACORAM for the mobile Cloud-Edge computing.
Huan Zhou+5 more
semanticscholar +1 more source