NIRC is based on the National Key Laboratory of Network and Switching Technology at Beijing University of Posts and Telecommunications. It has built a technology matrix across four AI domains—intelligent cloud networking, natural language processing, computer vision, and machine learning systems—dedicated to solving real‑world problems, creating top‑tier systems, publishing high‑impact papers, and contributing significantly to the rapid advancement of China's network technology.
MongoDB is an open‑source, C++‑based NoSQL document database that stores data as BSON documents in collections, offering schema‑less modeling, embedded structures, high scalability through sharding, and a rich set of CRUD commands for modern application needs.
DeepQueueNet combines discrete‑event and continuous simulation with deep neural networks to deliver highly accurate, generalizable, and GPU‑scalable network performance estimates at packet‑level granularity, outperforming existing DNN‑based estimators across diverse topologies and traffic scenarios.
LONGNET introduces dilated attention to enable Transformers to process sequences exceeding one billion tokens with linear computational cost, preserving performance on shorter inputs and demonstrating strong results on long‑sequence modeling and standard language tasks.
The article explains how the Anomaly Transformer leverages prior‑ and series‑association discrepancies, a learnable Gaussian kernel, and a Minimax training strategy to distinguish normal from abnormal points in time‑series data, achieving state‑of‑the‑art results on five benchmark datasets.
The article presents a neural‑algorithmic reasoning approach that replaces slow SMT‑based network configuration tools with a graph‑neural‑network model, describing dataset creation, model architecture, and experiments that show 20‑to‑490× speedups while maintaining over 92% configuration consistency on large topologies.
This tutorial walks through deploying a simple Hello World application on a Kubernetes cluster using YAML files, covering Deployment and Service definitions, key fields such as name, selector, labels, image, ports, and how to expose the service via a NodePort.
This article explains the principles of first‑generation biometrics, introduces finger‑vein recognition as a more secure alternative, and details a complete OpenCV workflow—including Gaussian smoothing, histogram equalization, edge detection, SIFT feature extraction, and knnMatch—to preprocess and match finger‑vein images.
This article explains GPT's two‑stage learning—unsupervised generative pre‑training on large raw corpora followed by discriminative fine‑tuning on labeled tasks—detailing the underlying Transformer decoder architecture, loss functions, and task‑specific input transformations.
This article presents NetShare, an end-to-end framework that uses time‑series GANs combined with domain‑specific encoding to synthesize privacy‑preserving IP header and flow traces, achieving up to 46% higher accuracy than prior generative baselines while improving the fidelity‑privacy trade‑off.
Vehicle networking transforms modern cars into complex, software‑driven systems that communicate via wireless links, and this article outlines its background, key research problems such as sensing, communication, decision‑making, the role of blockchain for security and transactions, platoon control, and digital twin applications for resource allocation.
