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WiFi 7 (Wi-Fi 7) is the next-generation Wi-Fi standard to be launched, also known as IEEE 802.11be — extremely high throughput (EHT). Based on Wi-Fi 6, Wi-Fi 7 introduces technologies such as 320 MHz bandwidth, 4096-quadrature amplitude modulation (QAM), multiple resource unit (MRU), multi-link operation (MLO), and multi-access point (AP) coordination. Drawing on these cutting-edge technologies, Wi-Fi 7 delivers a higher data transmission rates and lower latency than Wi-Fi 6. Wi-Fi 7 is expected to support a throughput of up to 23 Gbps, about three times that of Wi-Fi 6.
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CRC
Cyclic redundancy check (CRC) is a common data transmission error detection technique commonly used in the data communication field. The transmit end calculates a check code for the data in a data frame based on a certain algorithm, appends the check code to the data frame, and sends the data frame to the receive end. The receive end verifies the correctness and integrity of the received data by repeating the calculation using the same algorithm.
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QAM
Quadrature amplitude modulation (QAM) is an advanced modulation scheme widely used in Wi-Fi communication systems. It combines phase modulation and amplitude modulation.
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Segment Routing IPv6 (SRv6) is a next-generation IP bearer protocol that combines Segment Routing (SR) and IPv6. Utilizing existing IPv6 forwarding technology, SRv6 implements network programming through flexible IPv6 extension headers. SRv6 reduces the number of required protocol types, offers great extensibility and programmability, and meets the diversified requirements of more new services. It also provides high reliability and offers exciting cloud service application potential.
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Internet Protocol Security (IPsec) is a suite of protocols and services that provide security for IP networks. It is a widely used virtual private network (VPN) technology. IP packets lack effective security mechanisms and may be forged, stolen, or tampered with when being transmitted on a public network, such as the Internet. To solve this problem, the communicating parties establish an IPsec tunnel for encrypted transmission of IP packets. This ensures secure transmission of IP packets on an insecure network, such as the Internet.
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Telemetry is a next-generation network monitoring technology used to remotely collect data from devices at high speed. Devices periodically push device information to a collector, providing real-time, high-speed, and accurate network monitoring. To be specific, telemetry organizes data based on YANG models, encodes data in the Google Protocol Buffers (GPB) format, and transmits data through the Google Remote Procedure Call (gRPC) protocol. This improves data collection efficiency and facilitates intelligent interconnection. In traditional technologies, a collector and devices interact in pull mode by alternatively sending requests and responses. In contrast to these technologies, telemetry works in push mode and has the following advantages: - Proactively pushes data, reducing the pressure on devices. - Pushes data periodically in subseconds to avoid data inaccuracy caused by network delay. - Is capable to monitor a large number of network devices, improving network monitoring efficiency.
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VXLAN, or Virtual Extensible LAN, is a network virtualization technology widely used on large Layer 2 networks. VXLAN establishes a logical tunnel between the source and destination network devices, through which it uses MAC-in-UDP encapsulation for packets. Specifically, it encapsulates original Ethernet frames sent by a VM into UDP packets. It then encapsulates the UDP packets with the IP header and Ethernet header of the physical network as outer headers, enabling these packets to be routed across the network like common IP packets. This frees VMs on the Layer 2 network from the structural limitations of the Layer 2 and Layer 3 networks.
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What Is AAA? Three Elements of AAA
AAA
Authentication, Authorization, and Accounting (AAA) is a security management framework for network access control. It determines which users can access the network and which resources or services are available to authorized users. This document introduces the three elements of AAA and its implementation, used protocols, as well as applications.
What Is AI ECN? How Does AI ECN Differ from ECN?
The Artificial Intelligence Explicit Congestion Notification (AI ECN) function intelligently adjusts ECN thresholds of lossless queues based on the traffic model on the live network. This function ensures low delay and high throughput with zero packet loss, achieving optimal performance for lossless services.
What Is Adaptive Routing? Why Do We Need It?
Adaptive routing is a technology that dynamically determines routes based on the network topology and traffic load changes. By proactively detecting the link congestion status, adaptive routing preferentially selects a short and non-congested packet forwarding path to improve network throughput and resilience, as well as reduce network latency. Currently, adaptive routing and the direct topology are used together in large supercomputing centers.
What Is DNS? DNS Domain Name Resolution Process
DNS
TCP/IP uses IP addresses to connect to devices. However, memorizing the IP addresses of devices is difficult for users. As such, a host naming mechanism is used to match IP addresses with host names in the string format. DNS provides a translation and query mechanism between IP addresses and host names.
What is DPFR? Why do we need it?
DPFR is a sub-millisecond-level fault recovery technology. It can quickly detect port faults based on the data plane, and work with functions such as local fast fault convergence, remote fault advertisement, and remote fast fault convergence to implement fast fault rectification, without affecting services. This document describes why DPFR is required, comparison between DPFR and traditional fault convergence technologies, how DPFR works, and a typical application of DPFR.
What Is Embedded AI (EAI)? Why Do We Need EAI?
EAI
Embedded AI, also known as Embedded Artificial Intelligence (EAI), is a general-purpose framework system for AI functions. It is built into network devices and provides common model management, data obtaining, and data preprocessing functions for AI algorithm-based functions for these devices. In addition, it supports the function to send inference results to AI algorithm-based functions. This fully utilizes the sample data and computing capabilities of devices, while offering advantages such as lower data transmission costs, as well as ensured data security and real-time inferencing and decision-making.
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