5G Management Data Analytics Service for Traffic Prediction
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Solution Overview
Problem
The increasing complexity of 3GPP LTE networks due to diverse devices and data bandwidth demands, coupled with proprietary physical implementations, hinders flexibility in adapting to different network conditions, necessitating advanced management data analytics for performance optimization.
Innovation Solution
The implementation of a Management Data Analytics Service (MDAS) within the 5G network, which analyzes raw performance data to produce key performance indicators (KPIs) for predicting traffic volume and resource utilization, enabling proactive resource scaling and load balancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If Network Function Virtualization (NFV) is implemented to provide flexibility in configuring network objects, then adaptability to different network conditions improves, but device complexity increases due to virtualized environment and software applications
Solution Approach 1:
The patent introduces a Management Data Analytics Service as an intermediary layer between network devices and management systems. This service collects, processes, and analyzes performance data from virtualized network functions, providing simplified analytics capabilities without requiring direct complex interactions with the underlying NFV infrastructure. The analytics service acts as a mediator that translates complex virtualized environment data into actionable insights.
2Reliability
If proprietary physical implementations are used for network devices, then manufacturing precision and reliability improve, but adaptability to different network conditions deteriorates
Solution Approach 1:
The patent implements preliminary action by proactively analyzing performance data and predicting future network conditions before they manifest as problems. The Management Data Analytics Service continuously monitors and processes performance metrics, identifying trends and potential issues in advance. This allows the system to prepare and adapt to changing network conditions before they impact service quality, maintaining reliability while enabling adaptability.
3Productivity
If the number and diversity of communication devices increase to meet user demands, then productivity and service coverage improve, but network complexity and difficulty of management increase
Solution Approach 1:
The patent implements self-service through automated data collection, processing, and analysis capabilities within the Management Data Analytics Service. The system automatically gathers performance data from diverse network devices, processes this data through standardized protocols, and generates analytics without requiring manual intervention. This automation reduces the management burden despite increasing device diversity and network complexity, allowing the system to handle larger numbers of varied communication devices efficiently.
Data Source
AI summary
Systems and methods of providing a management data analytics service are described. After receiving a request for a management data analytical KPI, the MDAS producer determines from which of network objects to collect the performance measurements to generate the management analytical data. The network objects include an NF, NSI, NSSI, subnetwork or the network. Performance data is collected for a past period and management analytical data generated based on the collected performance data. The KPI for a future period related to the past period is determined. The KPI is to predict uplink or downlink traffic volume or resource utilization associated with the network object.