Results 31 to 40 of about 9,752 (300)

Security and Cost-Aware Computation Offloading via Deep Reinforcement Learning in Mobile Edge Computing [PDF]

, 2020
© 2019 Binbin Huang et al. With the explosive growth of mobile applications, mobile devices need to be equipped with abundant resources to process massive and complex mobile applications.
Huang, B, Xu, Y, Li, Z, Pan, L, Li, Y, Hu, H, Wang, S   +6 more
core   +1 more source

Adaptive secure malware efficient machine learning algorithm for healthcare data

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed, Abdullah Lakhan, Dilovan Asaad Zebari, Karrar Hameed Abdulkareem, Jan Nedoma, Radek Martinek, Usman Tariq, Majed Alhaisoni, Prayag Tiwari   +8 more
wiley   +1 more source

Cross-domain task offloading and computing resource allocation for edge computation in industrial Internet of things

物联网学报, 2020
In the industrial Internet of things,limited by the computing capacity of field devices,the task offloading based on edge computing can effectively alleviate the computing burden of field devices and provide low-latency computing services.Moreover ...
Peng ZHOU, Jincheng XU, Bo YANG
doaj   +2 more sources

A Survey and Taxonomy on Task Offloading for Edge-Cloud Computing

IEEE Access, 2020
Edge-cloud computing, combining the benefits of both edge computing and cloud computing, is one of the most promising ways to address the resource insufficiency of smart devices.
Bo Wang, Changhai Wang, Wanwei Huang, Ying Song, Xiaoyun Qin   +4 more
doaj   +1 more source

HAGP: A Heuristic Algorithm Based on Greedy Policy for Task Offloading with Reliability of MDs in MEC of the Industrial Internet

Sensors, 2021
In the Industrial Internet, computing- and power-limited mobile devices (MDs) in the production process can hardly support the computation-intensive or time-sensitive applications.
Min Guo, Xing Huang, Wei Wang, Bing Liang, Yanbing Yang, Lei Zhang, Liangyin Chen   +6 more
doaj   +1 more source

User privacy prevention model using supervised federated learning‐based block chain approach for internet of Medical Things

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract This research focuses on addressing the privacy issues in healthcare advancement monitoring with the rapid establishment of the decentralised communication system in the Internet of Medical Things (IoMT). An integrated blockchain homomorphic encryption standard with an in‐build supervised learning‐based smart contract is designed to improvise ...
Chandramohan Dhasarathan, Mohammad Kamrul Hasan, Shayla Islam, Salwani Abdullah, Shailesh Khapre, Dalbir Singh, Abdulaziz A. Alsulami, Ali Alqahtani   +7 more
wiley   +1 more source

A Task Oriented Computation Offloading Algorithm for Intelligent Vehicle Network With Mobile Edge Computing

IEEE Access, 2019
With the rise of intelligent and connected vehicles (ICVs), new vehicle applications continue to emerge, while the computing capability of vehicles remains limited.
Jun Liu, Shoubin Wang, Jintao Wang, Chang Liu, Yan Yan   +4 more
doaj   +1 more source

Joint Optimization of Computation Offloading and Task Scheduling in Vehicular Edge Computing Networks

IEEE Access, 2020
Resource-intensive applications on smart vehicles is posing difficulties to the use of traditional cloud computing for computation offloading in vehicular networks.
Jianan Sun, Qing Gu, Tao Zheng, Ping Dong, Alvin Valera, Yajuan Qin   +5 more
doaj   +1 more source

Joint Management of Wireless and Computing Resources for Computation Offloading in Mobile Edge Clouds

, 2021
We consider the computation offloading problem in an edge computing system in which an operator jointly manages wireless and computing resources across devices that make their offloading decisions autonomously with the objective to minimize their own ...
Josilo, Sladana,, Dán, György,
core   +1 more source

Optimizing strategy of computing off loading energy consumption based on Lagrangian method

Dianxin kexue, 2018
With the development of mobile network technology and the popularization and application of intelligent terminals,mobile edge computing has become an important application of cloud computing.Computing offloading strategy has become one of the key issues ...
Guangxue YUE, Youkang ZHU, Jiansheng LIU, Yasheng DAI, Zhenxu YOU, Hao XU   +5 more
doaj   +2 more sources