Intelligent Service Deployment Policy for Next-Generation Industrial Edge Networks
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Intelligent Service Deployment Policy for Next-Generation Industrial Edge Networks
Authors
Keywords
-
Journal
IEEE Transactions on Network Science and Engineering
Volume 9, Issue 5, Pages 3057-3066
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Online
2021-10-28
DOI
10.1109/tnse.2021.3122178
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Multiarmed-Bandit-Based Decentralized Computation Offloading in Fog-Enabled IoT
- (2021) Sudip Misra et al. IEEE Internet of Things Journal
- Energy-Efficient Task Offloading and Resource Allocation via Deep Reinforcement Learning for Augmented Reality in Mobile Edge Networks
- (2021) Xing Chen et al. IEEE Internet of Things Journal
- Delay-Aware and Energy-Efficient Computation Offloading in Mobile-Edge Computing Using Deep Reinforcement Learning
- (2021) Laha Ale et al. IEEE Transactions on Cognitive Communications and Networking
- A Neural-Network-Based Optimal Resource Allocation Method for Secure IIoT Network
- (2021) Pratik Goswami et al. IEEE Internet of Things Journal
- Blockchain-Enabled Adaptive-Learning-Based Resource-Sharing Framework for IIoT Environment
- (2021) Sarah Iqbal et al. IEEE Internet of Things Journal
- Collaborative AI-Enabled Intelligent Partial Service Provisioning in Green Industrial Fog Networks
- (2021) Abhishek Hazra et al. IEEE Internet of Things Journal
- Deep Reinforcement Learning-Based Adaptive Computation Offloading for MEC in Heterogeneous Vehicular Networks
- (2020) Hongchang Ke et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Multiagent Deep Reinforcement Learning for Joint Multichannel Access and Task Offloading of Mobile-Edge Computing in Industry 4.0
- (2020) Zilong Cao et al. IEEE Internet of Things Journal
- Intelligent Offloading for Collaborative Smart City Services in Edge Computing
- (2020) Xiaolong Xu et al. IEEE Internet of Things Journal
- A Data Set Accuracy Weighted Random Forest Algorithm for IoT Fault Detection Based on Edge Computing and Blockchain
- (2020) Wenbo Zhang et al. IEEE Internet of Things Journal
- Edge Server Quantification and Placement for Offloading Social Media Services in Industrial Cognitive IoV
- (2020) Xiaolong Xu et al. IEEE Transactions on Industrial Informatics
- Stackelberg Game for Service Deployment of IoT-Enabled Applications in 6G-Aware Fog Networks
- (2020) Abhishek Hazra et al. IEEE Internet of Things Journal
- Deep Reinforcement Learning Based Computation Offloading in Fog Enabled Industrial Internet of Things
- (2020) Yijing Ren et al. IEEE Transactions on Industrial Informatics
- Service Offloading With Deep Q-Network for Digital Twinning-Empowered Internet of Vehicles in Edge Computing
- (2020) Xiaolong Xu et al. IEEE Transactions on Industrial Informatics
- AI-Enhanced Offloading in Edge Computing: When Machine Learning Meets Industrial IoT
- (2019) Wen Sun et al. IEEE NETWORK
- A Multicharger Cooperative Energy Provision Algorithm Based on Density Clustering in the Industrial Internet of Things
- (2019) Guangjie Han et al. IEEE Internet of Things Journal
- Energy-Efficient Multiuser Partial Computation Offloading With Collaboration of Terminals, Radio Access Network, and Edge Server
- (2019) Min Sheng et al. IEEE TRANSACTIONS ON COMMUNICATIONS
- DPTO: A Deadline and Priority-Aware Task Offloading in Fog Computing Framework Leveraging Multilevel Feedback Queueing
- (2019) Mainak Adhikari et al. IEEE Internet of Things Journal
- Latency-Driven Parallel Task Data Offloading in Fog Computing Networks for Industrial Applications
- (2019) Mithun Mukherjee et al. IEEE Transactions on Industrial Informatics
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now