CRAWDAD umkc/networkslicing5g
收藏DataCite Commons2022-12-08 更新2025-04-16 收录
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https://ieee-dataport.org/open-access/crawdad-umkcnetworkslicing5g
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资源简介：
We have created a Deep Learning model for 5G and Network Slicing. (eMBB, URLLC, IoT).I encourage developers and researchers working on the 4G/LTE, 5G, 6G and similar interest to use and provide feedback:Our research can be found at1. IEEE paper "DeepSlice: A Deep Learning Approach towards an Efficient and Reliable Network Slicing in 5G Networks" (https://ieeexplore.ieee.org/document/8993066)2. IEEE paper "Secure5G: A Deep Learning Framework Towards a Secure Network Slicing in 5G and Beyond" (https://ieeexplore.ieee.org/document/9031158)date/time of measurement start: 2019-05-01date/time of measurement end: 2019-10-30measurement purpose: Computer Malware (Worms) Investigation, Energy-Efficient Wireless Network, Network Diagnosis, Network Performance Analysis, Network Security, Routing Protocol file: 5G_Dataset_Network_Slicing_CRAWDAD_Shared.zip
提供机构：
IEEE DataPort
创建时间：
2022-12-08
