Service Level Agreements By Requesting the administration of a few technologies, Artificial intelligence will play a key role without adding to the complexity of the network and service providers. for example, 4G, 5G, and IoT, as well as the growth of the number of connected gadgets.
- From the standpoint of the customer, this means that an ever-increasing range of services, such as video streaming via dominating services (OTT), are governed by autonomous AI algorithms. These components have resulted in the following research tools:
- Why, in specific situations, network service will not be unable to meet its service level agreement (SLA)?
- For what reason is 4G radio antenna coverage not enough to reach a particular service level agreement in a specific zone?
- How might we guarantee that energy efficiency measures are implemented while maintaining key performance indicators (KPIs)?
- How to guarantee protection from vulnerability and unexpected attacks?
This guarantees that our AI systems that manage the upcoming networks are powerful, secure, verifiable, and smart. At last, we accept that the more solid AI systems are, the quicker they will be endorsed.
Having The option to explain Artificial intelligence is disclosing to users how the AI system decides.
- How often have you asked why a video was automatically recommended to you on a video streaming service?
- Remember how stunned or disappointed with the recommendation after watching the video?
The objective of explainable Artificial intelligence (XAI) is to clarify the AI system’s recommendations or choices to make them more dependable.
We identify that explainability is an essential part of solid AI. So, we specify that an explainable Artificial intelligence system should generate details and the fundamental reasons behind its functions, processes, and results.
In telecommunications network operations, we are not looking at explaining things like movie recommendations. All things being equal, we consider the explainability of complex Artificial intelligence systems that usually comprise of a few parts of AI – sometimes called AI agents.
Consider the quality assurance of the video streaming service. This includes a huge number of complex errands where AI has gotten necessary:
We need to continually monitor and anticipate future traffic on the network to be prepared for expanded client demand, for instance – image a mass of individuals tuning into watching a new episode of a program at the same time.
On account of anticipated traffic spikes and in this way network congestion, we need to plan to reconfigure the network routers and, therefore, reallocate the network resources to keep serving the video stream without delay.
What’s more, we need to reallocate resources without unfavorably influencing other services running on the network, for example, automatic vehicle traffic signaling.
SLA-Based Services Apps that are supported by AI technology are recognized as creative platforms for managing and utilizing network field service processes.
What Role Does Network Operations play in Enabling 5G Resilient Systems?
It is common to hear about cyberattacks and security vulnerabilities affecting governments and enterprises. These attacks can take place as a result of state-sponsored or organized criminal acts, or against individuals or groups.
Mobile networks are increasingly seen as a strategic national substructure by governments around the world, which has led to a growing focus on how to make them easier to defend against attacks and other distractions.
Additionally, efforts are being made to minimize the use of technologies like 5G private networks and their enhanced security framework.
Examples include industrial automation, mission-critical communication, identity management, remote monitoring of assets, etc.
What is AI 5G and How Does it Work?
AI no longer serves as a good thing for 5G networks, but rather as an essential component in overcoming the immense complexity of 5G networks.
As a result of artificial intelligence and the data and automation capabilities it brings, a variety of emerging network ecosystems can be controlled in a way that humans cannot do alone.
As a result of 5G’s potential to transform networks, expectations are high. 5G promises high performance, low latency, bandwidth, and availability to service providers.
To meet this growing demand, 5G networks will need to be scalable – for example, zero and self-healing networks are already under development.
Intentional Network Operations and Artificial intelligence Forecasts for 5G and AI
The need for cost-effective network deployment becomes increasingly important as service providers offer 5G services to enterprises. Network slices are one way to do this.
Slicing the network at the end is a unique technology in 5G, which allows efficient, customizable services to be delivered. Different enterprise customers will be able to access different parts of the network and ensure they get the level of performance they pay for by disassembling the network.
In the future, networking will be driven by cognitive systems, where networks will utilize a blend of machine learning and reasoning, built on a knowledge base and machine logic.
The technique involves not only slicing networks but also operating complex networks since we often lack enough information or labels to train all possible scenarios.
However, using this approach, the machine can learn on its own and make important decisions without being instructed or trained to do so.
With all of these approaches and intentional operations, we believe that 5G will be as independent as possible. It will be an exciting time.
Operation of 5G Network Slicing Based on intent
To realize the full benefits of 5G, network slicing is crucial. By providing the right connections for the right use cases, network slicing allows service providers to manage scale and complexity, meet high and diverse customer expectations, and increase revenue through new services and business models.
Making this possible requires advanced automation and AI-powered solutions. As part of each 5G network slice, a service level agreement (SLA) is defined that reflects the customer’s business objectives.
Through SLA prediction, root cause isolation, and constraint resolution, these data are used as input to the network’s cognitive AI systems to align seamlessly with business intent.
We at ExtNoc. Supporting the Transition from 4G to 5G Wireless Networks.