Enterprise Mobility, Mobile Infrastructure
Article | June 16, 2023
Choosing the right 5G architecture is crucial for enhancing operations while keeping scalability and budget in mind. Learn whether SA or NSA is more suitable for your business needs with this article.
1. Introduction to 5G Network Architectures
2. What is 5G SA?
2.1 Characteristics of SA Architecture
2.2 Benefits of SA Architecture
3. What is 5G NSA?
3.1 Characteristics of NSA Architecture
3.2 Benefits of NSA Architecture
4. Factors to Consider When Choosing Between SA and NSA
4.1 Cost Implications of Each Architecture
4.2 Future Implications of Each Architecture
5. Conclusion
1. Introduction to 5G Network Architectures
Widespread implementation of 5G is transforming how businesses across verticals operate, providing enhanced speed, low latency, and massive connectivity. The advancements in 5G system architecture enable new use cases, from autonomous vehicles to smart cities.
There are currently two types of 5G network architecture, namely 5G standalone (5G SA) and 5G non-standalone (5G NSA). These two architectures differ in how they connect to the existing 4G infrastructure, the type of equipment required, and the level of network independence. Therefore, understanding the difference between SA and NSA is crucial for companies and organizations implementing 5G architecture.
2. What is 5G SA?
5G SA architecture is an entirely new technology that uses 5G core network architecture, independent of the current 4G LTE network. It has various use cases, such as combining 5G with AI and edge use cases.
2.1 Characteristics of SA Architecture
Independent Network: All components of the architecture, including the 5G core architecture, radio access network, and user equipment, are not reliant on any 4G technology.
High Performance: 5G SA architecture is optimized for high performance and low latency, enabling fast data transfer rates and near-instantaneous response times.
Distributed Architecture: This allows efficient resource allocation and dynamic management of network resources.
End-to-End Encryption: It provides end-to-end encryption, which ensures that data is secure and protected from unauthorized access.
Higher Cost: 5G SA architecture is more expensive to implement than NSA architecture due to the need for a fully independent 5G network infrastructure.
2.2 Benefits of SA Architecture
Low Latency: Applications of 5G that require real-time processing are only possible with SA architecture.
Customization: As SA does not depend on existing network architecture, it can be tailored to company requirements. It also enables network slicing for 5G enterprise private network use cases.
Security: End-to-end encryptions ensure a more secure network, and 5G network slicing keeps various access levels separate.
Scalability: 5G architecture is designed to be highly scalable and handle large volumes of data and devices.
Future-proofing: SA architecture will be able to support upcoming 5G features and capabilities by design.
3. What is 5G NSA?
5G NSA provides a transition into 'true' 5G architecture by incorporating 4G network infrastructure for deployment.
3.1 Characteristics of NSA Architecture
Non-Independent Network: 5G NSA architecture is designed to leverage the existing 4G infrastructure to deliver 5G services.
Transition to SA: NSA offers lower latencies and faster speeds than 4G LTE without deploying 5G architecture.
Integrated Deployment: 5G NSA can be deployed quickly since it integrates existing infrastructure.
Limited Scalability: As it relies on the existing 4G infrastructure, NSA is limited in scaling.
Low Scalability: There is a lower limit on how many devices can join the network and the data volume that can be processed on NSA.
3.2 Benefits of NSA Architecture
Faster Deployment: 5G NSA architecture can be deployed more rapidly than SA architecture.
Easier Integration: 4G integration with existing networks is easier since it uses architecture.
Cost-effective: 5G NSA architecture is generally less expensive to implement as it doesn't require a complete overhaul of the existing infrastructure to a 5G core architecture.
Improvement Over 4G: While not providing the speed and low latency of 'true' 5G, NSA offers significant improvements over 4G networks.
4. Factors to Consider When Choosing Between SA and NSA
4.1 Cost Implications of Each Architecture
SA architecture requires a complete overhaul of the existing infrastructure, which can result in higher infrastructure and deployment costs. However, SA architecture can be more cost-effective in the long run due to its future-proof design and ability to provide greater scalability and customization.
On the other hand, NSA architecture leverages the existing 4G infrastructure, resulting in lower infrastructure and deployment costs. However, upgrading and maintaining an existing 4G network to support 5G technology can be complex and may result in higher operational costs in the long run.
4.2 Future Implications of Each Architecture
SA architecture is designed to be future-proof and scalable, supporting upcoming 5G features and capabilities. This can give organizations greater flexibility and agility to respond to changing business needs and emerging technologies. On the other hand, NSA architecture may be less future-proof and require additional investments in infrastructure and resources to support new 5G features and capabilities.
5. Conclusion
While NSA architecture may offer lower upfront costs and a faster deployment timeline, SA architecture may be more future-proof and scalable in the long run. Choosing the appropriate 5G architecture is a critical determinant for organizations aiming to utilize 5G technology in building a connected industry of the future. Organizations must evaluate their requirements and consider each architecture's short and long-term costs and operational implications before making a decision.
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Enterprise Mobility
Article | June 15, 2023
Applications of AI/ML
Modern businesses are adopting Artificial Intelligence (AI) that encompasses disciplines like machine learning (ML), natural language processing (NLP), evolutionary computation, etc., to increase their productivity and management capabilities.
Companies like Qualcomm are using AI and machine learning to improve their customer experience.
“Across many industries, we are currently experiencing the creation of intelligent machines that is using AI to simulate smart behavior.”
-Dr. Vinesh Sukumar, Senior Director- Head of AI/ML Product Management at Qualcomm, ( in an interview with Media7)
The application of machine learning in networking is swiftly taking shape. However, as the problems in modern computer networks are getting tedious to handle, AI tools are being introduced to hard-carry their smooth functioning.
Let’s take a look at how network complexity impacts businesses:
Difference in Network Parameters
Different client devices like laptops, smartphones, CCTV cameras, etc., are connected to a single network. However, their requirements and parameters are different. Therefore, the IT team of the business needs to meet them without compromising the functionality and security of the network.
Users Prefer Wireless Networks
Wireless networks are more complex than wired ones. They perform dynamically depending on the number of users, applications, and other variables.
Impact of Cloud Computing
Most applications are now cloud-based, and such a network has multiple data entry points and requires more support.
User Experience
Deciphering root cause analysis, finding correlation and solutions becomes tedious without an AI/ML model. Complex patterns remain unanalyzed, and this creates a vacuum between the customer and the business.
What Does ML Bring to the Table?
Machine learning applications in networking correlate to solving four types of network problems: clustering, extraction, regression, and classification.
For classification and regression, ML clusters similar data and creates a gap between data groups. It then successfully maps a new set of data to a pre-set continuously valued output. As for extraction, it easily establishes a statistical relationship between the data it analyzes.
Machine learning applications in networking encompass the following:
Automation and Cognitive Computing
ML enables automation in data processing by eliminating the human error factor and constantly improving with time. It analyzes data, improves the productivity, security, and health of the network. Cognitive computing allows processing diverse data sets, detecting and finding root causes and common traits within the system.
Network Monitoring & Security
Network monitoring is used to solve problems in a large dataset by deciphering the hidden pattern in the data. It then predicts the outcome for clustered data, malware attacks, or impending network failure. It recognizes impending threats in time and sends out warnings. ML uses anomaly-based intrusion, misuse-based intrusion, or hybrid intrusion to prevent misuse, modification, unauthorized access, or malfunction.
Traffic Prediction, Classification, and Routing
Network traffic prediction is important to handle any mishaps proactively. Network analysis in machine learning is done by using Time Series Forecasting (TSF). By using a regression model solution, TSF finds a correlation between the traffic volume in the future and the traffic previously observed.
Traffic classification ensures Quality of Service (QoS), planning ahead for capacity, security, performance analysis, etc. It helps with proper resource utilization by pinpointing unnecessary traffic in a critical application.
Factors like cost-effectiveness, link utilization, operational capabilities, and policies are also considered by the ML model.
Congestion Control
ML models control the number of packets that enter a network to ensure that the network is stable, fairly utilize resources, and follow queue management employed for congestion control.
Efficiently Managing Resources
ML efficiently manages network resources like the CPU, frequency, switches, memory, routers, etc., by using analytical decision-making.
ML Learning Curve
ML models learn in the following ways:
Pitfalls
Like any other technology, machine learning application in networking comes with pitfalls and limitations. Here are a few:
Data Quality
The efficiency of an ML model is based on the quality, quantity, and diversity of data it processes so it can deduce patterns or identify root causes. Most ML models use simplistic synthetic data for training, validation, and performance. The same cannot be said about practical settings because the data comes from different applications and services and is more complex.
Feasibility
There are scalability and feasibility issues because each network and application is different. Moreover, there are no set standards for uniformity for implementation which makes it hard to set benchmarks or best practices. Control over autonomic networks is distributed and remains limited based on the vendor’s specific devices.
Predictive Analysis and Its Cost
Network analysis and machine learning prediction require additional accurate and effective monitoring investments. Moreover, fault management may have some potholes as there may be a scarcity of normal fault data.
High FPR (False Positive Rates)
Anomaly detection by ML in networking has not created enough buzz in the industry because it generates high FPRs during operations. Also, no detailed anomaly report is generated, so no anomaly history log can be maintained.
Striking a Balance
ML requires time to learn and mitigate issues. It is difficult to identify, in advance, how complex the ML’s approach will be. Striking a balance between the performance and computational cost is difficult. Deciphering comprehensive evaluation metrics is also a tedious task.
No Theoretical Model
There is no theoretical model, in turn, a unified theory, for ML in networking, so each network may have to be learned separately. The current machine learning applications in networking are made keeping in mind certain applications. Over time, more research to tailor ML for certain networks needs to be done. Cross-domain experts who understand both ML and networking are also rare.
Solutions
Software Defined Networking (SDN)
CISCO helped PwC Italy set up a secure network at their new twenty-eight-floor tower with the help of their SD-Access product. PwC wanted a secure, robust network with increased Wi-Fi and wired connectivity for their 3000 employees by streamlining network operations.
“We needed a robust and highly reliable wireless network infrastructure that’s as advanced as the tower itself.”
-Simone Demaria,Network Architect and Infrastructure Manager at PwC Italy
By applying Software Defined Network (SDN), IT personnel can remotely govern network policies in real-time through open interfaces, so traffic engineering is easily possible. SDN also contributes to network virtualization.
SDN supports the upcoming 5G ecosystem. When combined with NFV and VNF, SDN can revolutionize networking.
Going Beyond Traffic Volume & Prediction
To tackle the limitations that TSF-based traffic prediction models have, leveraging features beyond traffic prediction and concentrating on traffic interpolation and sampling could be viable. Research is ongoing on this possibility.
Summing It Up
As the influx of data keeps on increasing, the complexity of networks will increase in tandem. For successfully implementing ML for streamlining networking, the ML approaches we are aware of today need to be upgraded to accommodate multi-layer networks and multi-tenancy so autonomic networking can be a reality.
FAQs
How Can ML Help in Making Networking Smarter?
ML can streamline the network by automation, threat detection, and improving its performance.
How Complex Is Integrating ML into Networking?
The complexity depends on the type of network you are integrating it into.
What to Keep in Mind Before Using Ml in Networking?
Consider investment costs, data availability, feasibility, and scalability.
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Network Infrastructure, Network Management
Article | July 27, 2023
Something revolutionary that solves problems becomes a product or service with many trade secrets you cannot afford to let loose in the market. All small, medium, and large businesses worry about how vulnerable they are to threats as far as data sharing within the organization is concerned. This is where a private network comes in.
Every business wants to take a technological leap for scalability. Two of the factors that private networks address are independence from commercial carriers for the network and maintaining the privacy of trade secrets. This helps achieve long-term goals to scale your business.
Powering your enterprise private network with the futuristic speeds of 5G can help your business achieve two goals at once. Take a look at why 5G has now started to matter even more.
Why 5G?
By 2026, the 5G market will reach $667.90 billion, with a CAGR of 122.3% from 2021 to 2026. It is estimated to go beyond $1.87 trillion by 2030. This massive technological transition will forever change how we communicate, process information, and connect with the cloud. A boost in turnkey research and development is one of the vital benefits of 5G that will help your business be one step ahead in the market.
What Makes the 5G Enterprise Private Network Ideal for Small and Medium-Sized Businesses?
A private enterprise network is VPN, LAN, WAN, or cloud-based. High-speed internet and low-latency data sharing or transfer are achieved using fiber optics in a 5G EPN. Expect superior service security, network slicing, enhanced service quality, and no risk of network congestion. Design your 5G EPN as per the software integrations required for your small and medium-sized business. This will allow seamless integration for present and future needs.
5G is about 100 times faster than 4G, leading to incredible speeds and unlocking many never-seen-before possibilities accelerating the speed of research for your enterprise. The network efficiency and the traffic capacity it can handle are 100x. Connecting and sharing data in almost real-time is made possible with 5G.
This means, a private 5G network can reduce the infrastructure needs of relatively more demanding managed wired networks for small and medium-sized businesses supporting 5G ecosystems. But it will keep up with the most advanced wireless technologies of the future and stop supporting older ones. In addition, 5G supports lower power consumption than 4G during data transmission. This means enterprises get better battery life on devices running 5G, including 5G IoT devices.
How Secure is a 5G Enterprise Private Network?
The 5G enterprise private networks are integrated or hybrid EPNs (enterprise private networks) and independent EPNs. It depends on whether your business wants to lease 5G spectrum from the government or a mobile network operator (MNO) and whether you will use a hybrid or independent EPN.
• Integrated 5G EPN: A small business can lease a private 5G line from an MNO. A public 5G network backs a virtual private network (VPN) for medium-to-small businesses. On the other hand, MEC and UPF from a public 5G network are used to set up a local network for large businesses.
• Independent 5G EPN: This is the most secure type of 5G EPN, the independent 5G EPN. It is independently built for your enterprise, owned, operated, and managed by you. You will be handling the RAN, core, edge computing nodes, and the wireless spectrum reserved for your use. These are mostly the goals of a large business that sends and stores data that needs to be very secure.
An independent 5G EPN is the best solution for large enterprises looking for the most secure private network. Also, it applies to businesses dealing with massive amounts of data.
Why Use the Cloud for Storage and Retrieval of Data in 5G EPN?
Access computing resources, data storage, development tools, and applications across the internet with the help of the cloud. The combined features of 5G and a private enterprise network create a healthy environment to implement cloud infrastructure. When thinking about using the cloud to store and get data in a 5G EPN, keep in mind the good things about it.
Interconnected, shared resources
5G speed
Improved reliability
Increased data accessibility
Better privacy and security
Efficient connectivity
Now that we have learned networking fundamentals for a better 5G EPN are resolved with the help of the cloud, let us discover how it can help your business scale.
How Can Your Small, Medium, or Large Business Scale up With a 5G EPN Network Easily?
You can use a 5G enterprise private network, or EPN, to get the most important benefits for a small business.
Speed to promote an industrial digital transformation
IoT readiness
Better control over digital assets.
Improved security
Reliable coverage
Network slicing
Ultra-low latency
Improved bandwidth
Improved quality of service (QoS)
You will have complete control over configuring and customizing your EPN, managed independently by your in-house 5G networks. Explore the future avenues of 5G private networks in detail.
The Future of 5G Private Networks and Wi-Fi with Industrial Use Cases:
According to a study by RAN Research, by 2028, private 5G networks will generate about $23.5 billion, with 19% usage in the manufacturing industry and 12% of the network in the healthcare industry. The deployment of the 5G network and upgraded Wi-Fi standards will likely be saturated by 2024. Most of the investments would be towards upgrading the infrastructure and maintaining the network.
The goal of fierce competition among telecom network operators will be to gain rapid market share, bringing down the cost of usage. The new service providers will garner competition from telecom giants, while 5G private networks from different enterprises will still be dominant and mainstream in providing security, privacy, and data isolation.
Leading Industrial Use Cases
Healthcare: A revolution in healthcare benefiting from 5G technology is bound to happen with their transition to a cloud-native architecture. The need for high-speed and reliable connectivity will arise sooner or later, and 5G private networks will perfectly meet the requirement. The driving forces for healthcare to adopt 5G private networks include the shift to demographics, value-based and patient-centric care, and emergency healthcare. In addition, the use of big data analytics, the internet of medical things (IoMT), better wearable medical technology, hospital remote monitoring systems, e-Health and more will need the speed that 5G offers.
Manufacturing: The Industrial Internet of Things (IIoT) uses private 5G networks. Depending upon the software-defined implementation of the 5G network, 5G does not just allow remote monitoring of production lines; it also regulates maintenance and device lifecycle while powering industrial automation. 5G is also finding its way into implementing augmented reality for troubleshooting electronics, additive manufacturing and 3D printing, automated guided vehicles, camera-based video analytics and more. Collaborative robotics, supply chain optimization, and maintenance using a digital twin are a few other things that are worth mentioning.
Supply Chain: Due to near-shoring, manufacturing and distribution will decentralize. Due to Internet of Things (IoT) devices with sensors, supply chain and shipping logistics companies will be able to reduce delivery times, have better control over warehouse and transportation environments, and offer great asset management services.
Final Thoughts
Finding the right 5G private network type for your enterprise is easy. It offers enhanced security while connecting to the cloud, IoT and more. This would allow the development of futuristic products and services, touching multiple industries, with healthcare, manufacturing, warehousing, and logistics among the top. Keeping trade secrets and the latest research and development secure and enhancing the capabilities by integrating future technologies will improve with a 5G EPN. With a 5G private network for your enterprise being used on a large scale, the future of networking looks bright.
FAQs:
What is the difference between a public 5G network and a private 5G network?
A single location or several locations of the same institution, business, or organization are the focus of a private 5G network. On the contrary, the public 5G network is nationwide with millions of subscribers without being dedicated to serving a single entity. Because of this, 5G EPN infrastructure solutions will probably be used on college campuses, in factories, hospitals, military bases, transportation hubs, and other places.
What is a private 5G network and what are the benefits of a private 5G network?
A 5G private network offers low latency, high bandwidth and multiple connections with access control, which are perfect for business applications for small, medium and large enterprises. Furthermore, 5G private networks allow you to tailor them to your business requirements, making them an excellent investment for your business. Again, while diversifying your business as per customer and market demand, it is crucial to have a networking infrastructure that can adapt to your changing needs. Therefore, a private 5G network becomes even more critical.
How does EPN help in centralization and business continuity?
When implementing business continuity planning and centralization of your organization, a 5G EPN can provide several benefits over a public network. It makes integrations easy, provides high-quality services, improves access control and reliability, and lets your business share resources in the best way for its current and future needs.
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Article | July 7, 2021
Despite the COVID-induced interruptions in the first half of 2020, 5G preparations and deployment continued in earnest in the second half of 2020 and now the market – vendors, CSPS, OEMs – are ready to bring 5G to the masses of users. The arrival of Apple’s first 5G devices in 4Q20 marked the tipping point of global consumer readiness, now extending from early-adopters. After the initial phase of network launches that saw coverage built-out in major urban centres, 5G service providers should now focus on expanding coverage to as many areas of high-data demand as possible. At the same time, as CSPs gauge their 5G roll-out strategies, they shouldn’t ignore rural areas with limited-to-no high-speed broadband coverage. In many markets, particularly developing ones, CSPs should carefully assess network-sharing as a way to cost-effectively tap pent-up demand, especially given the accelerating remote working trend.
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