Powering AI at the Edge with Modernized Network Infrastructure

Today’s network infrastructures are undergoing a profound transformation, driven by the rapid proliferation of data and artificial intelligence (AI) at the edge. As agencies harness these technologies to their full potential, they face the critical challenge of modernizing their network infrastructures to be robust, scalable and agile.

Powering AI at the Edge with Modernized Network Infrastructure

This evolution is not merely about managing increased data volumes, but also about enabling smart, responsive and efficient operations across diverse environments. However, the journey toward network modernization requires careful navigation to avoid pitfalls that can lead to inefficiencies and increased costs. Misaligned investments and unvalidated network designs can derail modernization efforts. It’s crucial to select technologies tailored for the specific demands of AI at the edge and to validate network configuration designs to facilitate optimal network performance as data-driven devices increase. 

This blog explores the insights and strategies outlined in Meritalk’s research study, “The Future of Connectivity,” which highlights the path to successful network transformation. By adopting a multivendor approach and prioritizing scalability, security, and innovation, federal networks can evolve into dynamic assets capable of meeting current challenges and adapting to future opportunities. As agencies navigate these complexities, solutions like those from RUCKUS are instrumental in building resilient, efficient network infrastructures designed to thrive in the era of AI at the edge. 

Data Growth and AI at the Edge

According to the study, the explosion of data creation and consumption is driving network infrastructure modernization, necessitating a shift from centralized data center management to distributed edge computing. This approach places computing resources closer to where data is generated and utilized—facilitated by AI to enable real-time processing that minimizes latency and reduces bandwidth usage. This transformation mirrors the evolution seen in data centers moving to cloud computing. That is, in campus environments, there is a notable transition from traditional north-south traffic flows to east-west patterns. This shift reflects growing lateral data movement between devices and services within the network perimeter, fueled by collaborative AI-powered applications, internet of things (IoT) devices, and distributed computing. To keep pace with these changes, it’s critical for networks to efficiently manage complex, high-capacity traffic flows. 

As the number of AI-powered applications and connected IoT devices soars, more advanced Wi-Fi technology will be essential to unlocking the full potential of these end devices. Federal agencies are also focusing on modernizing Wi-Fi networks to keep up with evolving technology and demands of AI at the edge. However, this process comes with inherent risks that, if not carefully managed, can lead to inefficiencies and increased costs. Understanding these risks is key to successfully navigating the complexities of network modernization.

Risk 1: Investing in the Right Technology

One of the top risks in modernizing a network is investing in technology that does not align with the agency’s long-term goals and security requirements. For example, choosing Wi-Fi 6 as a short-term solution may meet immediate bandwidth needs, but it could fall short in the long run due to limitations in spectrum efficiency and scalability. On the other hand, opting for Wi-Fi 6E, which utilizes the 6 GHz spectrum, could introduce complexities and require significant infrastructure upgrades like cabling and switching improvements. Despite offering increased bandwidth, Wi-Fi 6E is still considered a steppingstone technology and it does not provide the efficient use of the increased spectrum that Wi-Fi 7 provides. These limitations can lead to potential compatibility issues and shorter product life cycle.

Similarly, federal agencies considering the adoption of open-source operating systems should prioritize rigorous evaluation and robust security measures. While open-source systems offer customization, community support, and integration capabilities, concerns about security persist. Unlike closed-source systems with tightly controlled proprietary security measures, open-source operating systems may face challenges related to vulnerabilities and the ability to effectively respond to threats in a timely manner. Agencies seeking to enjoy the benefits of open-source openness and community collaboration should also confirm their solution’s ability to meet stringent security standards. 

Finally, selecting a technology that cannot easily scale for future growth is an additional risk. As the number of computing devices at the edge multiplies, their network demands also increase—requiring technologies that can seamlessly accommodate additional users, devices, and data traffic. A Wi-Fi network that lacks scalability can become a bottleneck, leading to performance issues and necessitating costly overhauls. Agencies should choose a wireless technology that is inherently flexible (particularly with controller options) to adapt to a variety of deployments and administrative preferences. It is essential that the technology supports both centralized and distributed control models, allowing for tailored solutions that meet specific agency needs.

Risk 2: Design and Validation Challenges

Failing to adequately design and validate network configurations before implementation can also introduce risk. Poorly-positioned access points (APs) can result in coverage gaps or excessive interference, affecting network performance. For example, they could exacerbate co-channel interference issues due to the broader bandwidth, impacting overall reliability and user experience. Insufficient design validation may also overlook potential Wi-Fi issues such as signal attenuation in certain building materials, or unexpected environmental factors, necessitating costly adjustments post-deployment. Meticulous planning and testing can help agencies ensure optimal network performance and user satisfaction as data-driven devices populate the campus.

Importance of Planning

The risks associated with modernizing a Wi-Fi network underscore the importance of strategic planning and careful consideration of hardware and software technology choices. Investing in the wrong technology not only jeopardizes current operational efficiency but also sets the stage for future challenges, potentially requiring another round of costly refresh projects. Educating stakeholders is crucial to avoid short-sighted investments that do not align with a holistic view of the network and its future prospects—including advancements in AI, machine learning (ML), and edge computing enabled by advanced Wi-Fi solutions.  

Furthermore, conducting an active site survey for Wi-Fi is essential to meet service-level agreements (SLAs) for high throughput and low latency. Surveys help determine the best locations and configurations for APs, minimizing coverage gaps and reducing co-channel interference. By thoroughly mapping the RF environment and analyzing potential obstructions, they can help anticipate and mitigate factors that could impair Wi-Fi performance and slow data flow at the edge.

AI and ML at the Core of RUCKUS

Despite the risks, agencies simply cannot plan for everything. Network environments are dynamic, and unanticipated challenges are inevitable. Poor planning or unforeseen circumstances can significantly impact network performance, but this is where AI and ML come into play. RUCKUS understands the unpredictability of network demands and has engineered its solutions to adapt and thrive in such conditions, maintaining peak performance in conditions where traditional networks might struggle.

  • BeamFlex+® patented adaptive antenna technology intelligently directs Wi-Fi signals toward client devices. Unlike static antenna systems, BeamFlex+ technology dynamically adjusts the signal path based on the client’s location and orientation. This capability is crucial in environments where devices are constantly moving—providing robust and reliable connectivity. Using AI and ML principles, BeamFlex+ technology continuously learns from the surrounding RF environment, optimizing signal direction and reducing packet loss. This results in enhanced network performance and a superior user experience, even in high-density and high-interference scenarios. 
  • ChannelFly® software leverages AI and ML to optimize channel selection. Traditional networks often rely on static or manually-configured channels, which can lead to suboptimal performance as conditions change. ChannelFly software, however, dynamically analyzes the RF spectrum and predicts the best channels in real time. This proactive approach minimizes interference and maximizes throughput—providing a seamless, high-quality experience, particularly in congested environments where channel conditions can change rapidly. 
  • For agencies that can utilize cloud-based solutions, RUCKUS extends its AI capabilities to the cloud. RUCKUS AI includes cloud-based radio resource management, which efficiently manages spectrum use by dynamically adjusting to environmental conditions. This cloud-based intelligence helps ensure optimal performance and efficient resource utilization across the network, making it ideal for complex deployments that require scalable, adaptable solutions.

RUCKUS is leading the charge in Wi-Fi innovation. RUCKUS® solutions are purpose-built to handle the heavy data flows and complex demands of modern applications. Our products are built to last and to be future-proof and ready to meet the needs of ongoing network modernization efforts. RUCKUS products with Wi-Fi 6 technology meet the rigorous demands of today’s high-data applications, providing reliable, high-speed connectivity. Likewise, RUCKUS is also at the forefront of Wi-Fi 7 advancements. Wi-Fi 7 introduces groundbreaking features like multi-link operation (MLO), which enables simultaneous transmission across multiple channels and bands—drastically improving throughput and reducing latency. Innovations like Punctured Transmission and the expanded 6 GHz band enhance spectral efficiency and data rates, making these technologies pivotal for AI at the edge applications that demand swift and reliable connectivity.

RUCKUS AI-driven solutions epitomize the concept of using AI to empower AI. By integrating sophisticated AI and ML technologies, RUCKUS not only meets today’s connectivity challenges but also anticipates and adapts to future demands.

The Future Is Edge-Centric

As AI continues to push data processing to the edge, Wi-Fi will become increasingly important. RUCKUS Wi-Fi stands at the forefront of this evolution with its advanced technologies and AI-driven features, uniquely positioned to meet the demands of this new era. Its purpose-built design for high capacity, low latency, and adaptive performance makes it the ideal choice for agencies looking to modernize their network infrastructure and harness the full potential of AI at the edge.

In “The Future of Connectivity,” Meritalk delves deeper into the strategies and insights essential for federal agencies embarking on the journey of network modernization. By adopting a multivendor approach and prioritizing scalability, security, and innovation, agencies can transform their networks into agile assets capable of supporting today’s challenges and anticipating tomorrow’s opportunities. This approach not only enhances operational efficiency but also prepares for the AI-driven future.

With RUCKUS, the future of wireless connectivity goes beyond technological progress; it represents leadership in creating a smarter, more connected world. Discover how RUCKUS solutions can assist your agency in modernizing its network and integrating AI at the edge. Contact our federal sales team to learn more. 

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