AI 용어집
인공지능 완전 사전
Network Slicing
Virtualization technology enabling the creation of multiple independent virtual networks on a shared physical infrastructure, each tailored to specific service requirements.
MEC (Multi-access Edge Computing)
Edge computing architecture standardized by ETSI that provides computing and storage capabilities within the radio access network, close to end users.
NFV (Network Function Virtualization)
Approach involving virtualizing network functions traditionally run on dedicated hardware, allowing their flexible and dynamic deployment on cloud infrastructures.
RAN Intelligence Controller
Centralized logical entity that uses AI to optimize radio access network parameters in real time, including resource allocation and interference management.
Massive MIMO
Multi-antenna technology that uses tens or hundreds of antennas to serve multiple users simultaneously, significantly increasing the network's spectral capacity.
Traffic Offloading
Process of intelligently transferring network traffic from the core network to the edge or other networks to optimize resource usage and reduce congestion.
Resource Allocation
Distributed AI mechanism that dynamically optimizes the allocation of spectral, computing, and storage resources based on service requirements and network conditions.
QoS (Quality of Service)
Set of techniques and mechanisms that ensure specific performance levels for different types of network traffic, essential for critical applications.
Network Orchestration
Automation and coordination of complex network services, resources, and functions, often managed by AI to optimize end-to-end performance.
Distributed AI
Paradigm where AI models are distributed across multiple edge nodes, enabling collaborative learning and local decision-making without full centralization.
Network Function Chaining
Mechanism that sequentially connects different virtualized network functions to create a personalized end-to-end service, optimized by AI for 5G/6G flows.
Intelligent Traffic Management
AI-based system that analyzes and optimizes network traffic flow in real-time, prevents congestion and dynamically adapts transmission routes.
Zero-touch Network
Concept of a fully automated network where AI manages service deployment, configuration, and maintenance without human intervention.
Edge-native Applications
Applications specifically designed to run on edge infrastructures, leveraging low latency and local processing for optimal performance.
Network Edge Virtualization
Virtualization technique specifically applied to network edge equipment, enabling simultaneous execution of multiple functions and services on the same hardware.
AI-driven Network Slicing
Use of artificial intelligence to dynamically create, manage and optimize network slices based on service requirements and real-time conditions.