Clicky

Guavus Revs Up Open NWDAF to Spur Automated Multi-vendor 5G Networks
by Ron Westfall | June 15, 2021

The News: Guavus announced a new 5G network data analytics product designed to enable mobile operators to overcome the challenges of operating complex, multi-vendor 5G networks at scale and deliver new revenue-generating 5G services. Guavus 5G-IQ NWDAF is designed as a vendor-agnostic 3GPP-compliant NWDAF implementation that embodies an open approach to streaming analytics, machine learning (ML), and artificial intelligence (AI) for generating the real-time operational intelligence needed to drive service orchestration and network automation in the 5G Core (5GC).

The new product is developed to interoperate with all 3GPP-standard components in a 5G System – independent of supplier – while supporting the wide range of analytics-driven use cases that are critical to the diverse functional and operational requirements of 5G Standalone (SA) networks. Read the Guavus release here.

Guavus Revs Up Open NWDAF to Spur Automated Multi-vendor 5G Networks

Analyst Take: Guavus is meeting the topmost demands of operators with the Guavus 5G-IQ NWDAF launch. 5G’s architecture, especially 5G SA, brings new challenges to operators in areas such as fulfilling the latency requirements of mission-critical applications, supporting the massive increase in connections and devices, and adhering to stringent SLA requirements. To underpin meeting these new challenges, operators are adopting a cloud native infrastructure that takes advantage of 5G new radio (5G NR), 5G edge computing, and 5GC capabilities to leverage diverse and multi-vendor ecosystems in using innovations like network slicing to dynamically deliver emerging services like private 5G networks and 5G fixed wireless access (FWA).

I see 5G operations requiring closed loop network automation to successfully meet 5G’s distinct challenges. For starters, 5G networks will operates at scale and complexity substantially beyond 4G/LTE networks. As a result, analytics-driven machine intelligence is essential for implementing closed loop network automation. In contrast, operator-centric, vendor-proprietary analytical and monitoring solutions are not purpose-designed for automation environments. I view 5G network automation requirements as warranting the ecosystem-wide adoption of multi-vendor 5GC/RAN infrastructure that puts highest priority on the need for standards-based analytics and automation.

As such, 5G network architectural realities and market conditions bring together the architectural framework (i.e., 3GPP, 5G SBA), operating models (ETSI, TM Forum), standardized analytics (3GPP + O-RAN), and Open APIs (3GPP, 5G SBI) key to advancing the adoption of standards-based automation. In addition, through machine intelligence powering autonomous networks, operators attain the self-monitoring, self-analyzing, and self-driving capabilities to assure the readiness of standards-based automation in production networks.

The Joy of NWDAF: Ready to Drive 5G Orchestration and Automation

NWDAF provides the real-time intelligence, data collection, and analytics & AI/ML capabilities needed to execute the automated orchestration of 5GC functions and network controllers. NWDAF is specified in 3GPP TZS 29.250 as an integral part of the 5G Service-base Architecture (SBA), whereby the control plane functionality and common data repositories of a 5G network are delivered by way of a set of interconnected Network Functions (NFs), each with authorization to access each other’s services.

This includes leveraging OAM (Operations, Administration, Management) layer data analytics such as fault management, service assurance, and performance management to deliver comprehensive network-wide 5G orchestration. Through NWDAF, operator data collection and analytics platforms collect local data from NFs and Application Functions (AFs) to ensure the delivery of standardized analytics outputs to requesting NFs and real-time operational intelligence performance.

I anticipate that NWDAF will prove vital to productizing analytics, orchestration, and automation functions throughout 5G networks and ecosystems. Key benefits include reducing the level of customized system integration common to legacy, proprietary implementations and enabling operators to select the solutions best suited to their specific deployment needs.

Moreover, the NWDAF use case framework can improve service experience by enabling metrics by user, application, and service type as well as tracking by application type, device group, or geo-location. Factor in device behavior insights that track mobility patterns and detect abnormal usage in combination with network condition awareness such as performance, workload & anomaly tracking, and QoS sustainability and operators can combine current/past state statistical analytics with future state predictive analytics to optimize business and network performance outcomes.

With NWDAF, operators can capitalize on emerging 3GPP Release 16 use cases such as service experience computation and prediction for an application or UE (User Equipment) group (service experience), UE communication analytics and pattern prediction (device behavior), and network performance computation and prediction (network conditions).

Guavus 5G-IQ NWDAF: Open NWFAF Solution Set to Automate 5G SA Networks

I expect that the new Guavus 5G-IQ NWDAF solution will make significant inroads into operator 5G network deployments, particularly in providing Open NWDAF for complex, multi-vendor SA implementations. Operators need a NWDAF solution that assures a vendor-agnostic approach for securing interoperability with both 3GPP-compliant 5GC functions and non-standard components, as they transition toward open 5G models. The solution uses a cloud-native, container-based design for deployment both on-premise and on the public cloud.

The Guavus 5G-IQ NWDAF solution addresses operator edge to core to cloud requirements assuring the flexibility, scalability, and extensibility crucial to service agility and advancing cloud journeys. I view these features as ensuring operators can confidently select from multiple deployment options to meet the demands of the operational environment and service context. Moreover, scalability is achieved through high-performance data collection, aggregation, and scoring at the 5G edge and extensibility by supporting the plug-in of non-native analytics algorithms.

Key Takeaways on Guavus 5G-IQ NWDAF Launch

Overall, I believe the Guavus 5G-IQ NWDAF solution is well-positioned to power accelerated operator adoption of standards-based analytics, particularly in 5G SA environments. The solution’s built-in vendor-agnostic approach eases interoperability across multi-vendor 5G SA networks and provides operators the ability to procure, deploy, and manage a single NWDAF product. This further differentiates Guavus’ NWDAF solution from rival products integrated into broader solutions that increase risk of vendor lock-in and can render interoperability more difficult. Factor in Guavus’ existing business relation and NWDAF collaboration with AWS and Guavus stands out among a wide sea of competition.

Disclosure: Futurum Research is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.

Other insights from Futurum Research:

Guavus-IQ’s Availability on AWS Cloud is a Definitive Smart Move by Guavus

IBM Think 2021 Zeros in on AI, Hybrid Cloud and Ecosystem Growth

Oracle Database 21c: Powering Blockchain and AutoML Innovations

Image Credit: MarTech Series

About the Author

Ron is an experienced research expert and analyst, with over 20 years of experience in the digital and IT transformation markets. He is a recognized authority at tracking the evolution of and identifying the key disruptive trends within the service enablement ecosystem, including software and services, infrastructure, 5G/IoT, AI/analytics, security, cloud computing, revenue management, and regulatory issues. Read Full Bio.