SD-WAN helps improve AI system performance

AI system is a system that utilizes artificial intelligence (AI) technology to perform complex tasks. To achieve rapid training and deployment of AI, a high-speed, stable, and secure network infrastructure is required to support it. Due to its complexity, inefficiency, expense, inflexibility and other shortcomings, traditional wide area networks (WAN) have been unable to meet the network requirements of AI. Therefore, software-defined wide area network (SD-WAN), as an emerging enterprise networking solution, is particularly important.

Artificial Intelligence (AI) is one of the most innovative and promising technologies today, and it can bring tremendous value and efficiency to all walks of life. An AI system is a system that utilizes artificial intelligence (AI) technology to perform complex tasks, such as speech recognition, image analysis, or autonomous driving. To achieve rapid training and deployment of AI, a high-speed, stable, and secure network infrastructure is needed to support it. Due to its complexity, inefficiency, expense, inflexibility and other shortcomings, traditional wide area networks (WAN) have been unable to meet the network requirements of AI. Therefore, software-defined wide area network (SD-WAN), as an emerging enterprise networking solution, is particularly important.

SD-WAN is a network technology that dynamically selects the best path to transmit data packets, thereby improving network performance and reliability. SD-WAN can provide AI systems with faster, more stable, more secure, more flexible, and more efficient network connections because it can automatically select the most appropriate transmission method based on real-time network conditions and application requirements. For example, if an AI system requires a large amount of data and computing resources from the cloud, SD-WAN can direct the traffic directly to the cloud service provider without going through a traditional data center. This reduces latency and congestion and improves user experience and efficiency.

SD-WAN can help the AI ​​system get the cloud computing and edge computing support it needs. These technologies can allow the AI ​​system to perform different tasks in different locations, thereby achieving distributed intelligence. For example, an autonomous driving system can perform real-time perception and decision-making tasks on the vehicle, coordination and control tasks on the edge device, and learning and optimization tasks in the cloud. SD-WAN can distribute traffic to the nearest or most appropriate cloud or edge node based on the characteristics of each task. This reduces cost and energy consumption and improves scalability and security.

Using SD-WAN to assist and improve AI system performance has the following main advantages:

• Improve user experience and efficiency: SD-WAN allows the AI ​​system to quickly obtain the required data and computing resources, thereby reducing latency and congestion and improving response speed and accuracy.

• Reduce costs and energy consumption: SD-WAN allows AI systems to utilize the most economical or nearest cloud or edge node to perform tasks, thereby saving bandwidth and equipment expenses and reducing energy consumption.

• Improved scalability and security: SD-WAN allows AI systems to easily adapt to changing needs at different scales or scenarios, with protection from SASE to prevent data leakage or system corruption.

Let’s give some practical examples to illustrate:

• An AI system that uses speech recognition and natural language processing technology needs to obtain a large amount of speech and text data from the cloud, analyze and deal with. SD-WAN can select the best network path and bandwidth based on the content and priority of data packets, thereby reducing latency and packet loss, and improving the accuracy and efficiency of speech recognition and natural language processing.

• An AI system that uses image analysis and machine learning technology needs to perform real-time image processing tasks at edge nodes and send the results to the cloud for storage or further analysis. SD-WAN can select the closest or strongest network connection based on the location and performance of edge nodes, thereby reducing network overhead and energy consumption and improving the speed and quality of image analysis and machine learning.

• An AI system using autonomous driving technology needs to perform complex navigation and control tasks inside the vehicle and interact with the external environment. SD-WAN can select the most reliable or secure network connection based on the vehicle's driving status and surrounding conditions, thereby reducing risks and interference and improving the safety and reliability of autonomous driving technology.

To sum up, with the empowerment of SD-WAN technology, the AI ​​experience in different scenarios will be smoother. So how to ensure the security of data access and transmission?

SASE is the abbreviation of Secure Access Service Edge. It is a network architecture that integrates SD-WAN and cloud security services. SASE secures SD-WAN and AI systems because it dynamically delivers the most appropriate security policies and controls based on the identity and context of users, devices, applications, and data. For example, if an AI system needs to access a sensitive cloud database, SASE can encrypt, authenticate, authorize, and audit the traffic to prevent data leakage or tampering. If an AI system encounters a network attack or abnormal behavior, SASE can detect, isolate, respond, and recover the traffic to prevent system crash or damage.

Today, many companies have begun to use SASE to improve their network and security capabilities. For example, Lingrui Lanxin's new generation data security (SASE) access platform exquisitely integrates SD-WAN network technology and network security technology to form a new architecture based on SD-WAN SD-Security , and modularizes network and security functions. Based on SD-WAN network capabilities such as dynamic routing, multi-link integration, load balancing, UDP/TCP optimization, etc., it aggregates ZTNA zero-trust access, DDOS protection, malicious code protection, NGFW firewall, Security functions such as DNS protection are orchestrated, controlled, and scheduled through the controller to meet customers' secure access needs in multiple scenarios. The underlying data transmission uses the SecHX independent controllable security encapsulation protocol, which not only ensures the security of data transmission but also improves Data transmission efficiency.

According to Gartner predictions, by 2024, at least 40% of enterprises will adopt the SASE architectural model to support their digital transformation. This shows that SASE is one of the important trends in future network and security development.

To sum up, SD-WAN, as a mature enterprise networking solution, has significant advantages in improving AI network performance and security. In the future, with the further development and integration of SD-WAN and AI technologies, more innovation and value will be generated in fields such as cloud computing and edge computing.

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