Proactive Network Operations Using Multi-Scenario Event Prediction
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Solution Overview
Problem
Current communication networks operate reactively, leading to operational delays and unnecessary outages due to unpredictable events, and existing proactive methods rely on unrealistic assumptions, resulting in mispredictions and inefficient resource usage.
Innovation Solution
Implement proactive network operations by identifying multiple potential future events and concurrently starting processes that are alternatives to each other, executing them to an extent commensurate with their probability of occurrence, and adjusting based on changing probabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If reactive network operations are used, then network functions can be executed in response to triggers, but execution time is delayed and operational responsiveness deteriorates
Solution Approach 1:
The patent applies preliminary action by predicting future network events and pre-executing relevant network functions before the actual events occur. The system uses machine learning models to forecast events such as handovers, beam blockages, or UPF selections, and proactively executes preparation steps in advance, thereby reducing execution time and improving responsiveness when the predicted events actually happen.
2Loss of time
If proactive network operations are implemented without probability assessment, then response time is reduced, but resource wastage increases due to mispredictions
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the extent of proactive process execution based on predicted event probabilities. Instead of always executing full processes, the system modifies execution parameters (extent, duration, resource allocation) according to the confidence level of predictions, thereby reducing resource wastage on low-probability events while maintaining quick response for high-probability scenarios.
Solution Approach 2:
The patent applies partial action by executing network processes to varying extents based on predicted probabilities. For high-probability events, more extensive preparation is performed, while for low-probability events, only minimal or no action is taken. This selective execution approach prevents resource wastage on unnecessary operations while ensuring adequate preparation for likely scenarios.
3Reliability
If multiple alternative processes are executed proactively, then network responsiveness is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex set of alternative network processes into manageable, modular process templates. Each template represents a specific network function (handover, beamforming, UPF selection) that can be independently executed. This modular approach reduces management complexity by providing standardized, pre-defined process units rather than requiring custom coordination of multiple alternative operations.
Data Source
AI summary
A method, apparatus and system for proactively performing operations in a network, to prepare for potential future events. For each of multiple potential future events which are alternatives of one another, a value indicative of probability of the event occurring is determined. Then, a corresponding process is begun prior to occurrence of the event. The process is performed to an extent which is an increasing function of the probability of the event. The process accommodates requirements related to the event. Applications to mobile device handover and user plane function selection are included.