Results 51 to 60 of about 4,428,940 (290)

Research and development of virtualization in Wireless sensor networks

JOIV: International Journal on Informatics Visualization, 2018
Virtualization is foundational for applying both cloud computing and big data. It provides the basis for many platform attributes required to access, store, analyze, and manage the distributed computing components in big data environments. Virtualization
M. Sandeep Kumar, Prabhu. J
doaj   +1 more source

Virtual Width Networks

CoRR
We introduce Virtual Width Networks (VWN), a framework that delivers the benefits of wider representations without incurring the quadratic cost of increasing the hidden size. VWN decouples representational width from backbone width, expanding the embedding space while keeping backbone compute nearly constant.
Seed, Li, Baisheng, Wu, Banggu, Ma, Bole, Xiao, Bowen, Zhang, Chaoyi, Li, Cheng, Wang, Chengyi, Xu, Chengyin, Zhang, Chi, Hu, Chong, Zan, Daoguang, Zhu, Defa, Xu, Dongyu, Li, Du, Wu, Faming, Xia, Fan, Zhang, Ge, Shi, Guang, Chen, Haobin, Zhu, Hongyu, Huang, Hongzhi, Zhou, Huan, Dou, Huanzhang, Duan, Jianhui, Lu, Jianqiao, Jiang, Jianyu, Xu, Jiayi, Chen, Jiecao, Chen, Jin, Ma, Jin, Su, Jing, Chen, Jingji, Wang, Jun, Yuan, Jun, Liu, Juncai, Zhou, Jundong, Hua, Kai, Shen, Kai, Xiang, Kai, Chen, Kaiyuan, Liu, Kang, Shen, Ke, Xiang, Liang, Yan, Lin, Luo, Lishu, Zhang, Mengyao, Ding, Ming, Zhang, Mofan, Liang, Nianning, Li, Peng, Huang, Penghao, Mu, Pengpeng, Huang, Qi, Ma, Qianli, Min, Qiyang, Yu, Qiying, Pang, Renming, Zhang, Ru, Yan, Shen, Yan, Shen, Zhao, Shixiong, Cao, Shuaishuai, Wu, Shuang, Chen, Siyan, Li, Siyu, Qiao, Siyuan, Sun, Tao, Xin, Tian, Fan, Tiantian, Huang, Ting, Fan, Ting-Han, Jia, Wei, Zhang, Wenqiang, Liu, Wenxuan, Wu, Xiangzhong, Zuo, Xiaochen, Jia, Xiaoying, Yang, Ximing, Liu, Xin, Yu, Xin, Bin, Xingyan, Hao, Xintong, Luo, Xiongcai, Li, Xujing, Zhou, Xun, Peng, Yanghua, Chen, Yangrui, Lin, Yi, Leng, Yichong, Li, Yinghao, Song, Yingshuan, Ma, Yiyuan, Shan, Yong, Xiang, Yongan, Wu, Yonghui, Zhang, Yongtao, Yao, Yongzhen, Bao, Yu, Yang, Yuehang, Yuan, Yufeng, Li, Yunshui, Xian, Yuqiao, Zeng, Yutao, Wang, Yuxuan, Hong, Zehua, Wang, Zehua, Wang, Zengzhi, Yang, Zeyu, Yin, Zhengqiang, Lu, Zhenyi, Zhang, Zhexi, Chen, Zhi, Zhang, Zhi, Lin, Zhiqi, Huang, Zihao, Xu, Zilin, Wei, Ziyun, Wang, Zuo   +118 more
openaire   +2 more sources

SplitBox: Toward Efficient Private Network Function Virtualization [PDF]

, 2016
This paper presents SplitBox, an efficient system for privacy-preserving processing of network functions that are outsourced as software processes to the cloud.
Laurent Mathy, De Cristofaro, Emiliano, Soldani, C, Luca Melis, Cyril Soldani, Melis, L, Mohamed Ali Kaafar, Soldani, Cyril, Kaafar, Mohamed Ali, Emiliano De Cristofaro, Mathy, Laurent, Kaafar, MA, Hassan Jameel Asghar, Asghar, H, De Cristofaro, E, Mathy, L, Asghar, Hassan, Melis, Luca   +17 more
core   +1 more source

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

Arthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein, David J. Hunter, C. Kent Kwoh, Wolfgang Wirth   +3 more
wiley   +1 more source

Survey on network function virtualization in RAN

Dianxin kexue, 2019
Network function virtualization (NFV) is a kind of new network technology rising in recent years. It realizes the decoupling of software and hardware by running the software which has specific function on a general-purpose hardware server.
Haiyu JIA, Jia CHEN, Mingxin WANG
doaj   +2 more sources

Impact of Modern Virtualization Methods on Timing Precision and Performance of High-Speed Applications

, 2019
The presented work is a result of extended research and analysis on timing methods precision, their efficiency in different virtual environments and the impact of timing precision on the performance of high-speed networks applications.
Kirill Karpov, Oksana Vasylenko, Dmitry Kachan, Irina Zander, Sergii Maksymov, Eduard Siemens, Veronika Kirova   +6 more
core   +1 more source

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +1 more source

A Systematic Literature Review of Reliable Provisioning for Virtual Network Function Chaining

Applied Sciences, 2023
The abstraction of the network node functions using virtualization methods introduced an innovative architecture called Network Function Virtualization (NFV).
Le Duytam Ly, Mahsa Sadeghi Ghahroudi, Victor Ponce   +2 more
doaj   +1 more source

Virtual Network Embedding without Explicit Virtual Network Specification

CoRR, 2023
Network virtualization enables Internet service providers to run multiple heterogeneous and dedicated network architectures for different customers on a shared substrate. In existing works on virtual network embedding (VNE), each customer formulates a virtual network request (VNR) where a virtual network (VN) is required.
Jiangnan Cheng, Yingjie Bi, Ao Tang
openaire   +2 more sources

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source