Automated Network Change Scheduling System
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Solution Overview
Problem
Manual coordination of network changes across 5G/LTE/cloud networks is time-consuming, laborious, and error-prone, leading to potential service and network performance impacts due to conflicts between different work groups, layers, and end-to-end service paths, making it difficult to schedule maintenance activities without overlapping conflicts.
Innovation Solution
A scalable approach that models conflict rules and constraints using policies and algorithms to determine an optimized schedule for network change deployment, avoiding conflicts by obtaining requests for network changes, gathering information from various systems, and generating a conflict-free schedule that considers multiple constraints and constraints across virtual and physical network functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual coordination is used to schedule network changes, then flexibility in scheduling is maintained, but time consumption and error rate increase significantly
Solution Approach 1:
The system enables self-service scheduling by allowing network functions to automatically declare their change requirements and constraints. The automated scheduler then independently processes these declarations, resolves conflicts, and generates schedules without requiring manual coordination between different work groups, thereby eliminating the time-consuming manual coordination process while maintaining scheduling flexibility through automated policy-based decision making
Solution Approach 2:
The patent replaces the mechanical manual coordination process with an automated computational scheduling system. The scheduler uses algorithms to process change requests, resolve temporal and resource conflicts, and generate optimized schedules automatically. This substitution of manual mechanical coordination with automated computational mechanisms significantly reduces time consumption and error rates while maintaining scheduling flexibility through programmable policies
2Ease of operation
If manual coordination is used to schedule network changes, then scheduling flexibility is maintained, but labor requirements increase significantly
Solution Approach 1:
Network functions perform self-service by automatically declaring their change requirements, constraints, and preferred timing. The automated scheduler processes these self-declarations and independently resolves scheduling conflicts without requiring human labor for coordination. This self-service mechanism maintains scheduling flexibility through automated policy-based decision making while dramatically reducing labor requirements
Solution Approach 2:
The system changes the fundamental parameters of scheduling from manual human coordination to automated computational processing. By transforming scheduling parameters into structured data formats that can be processed algorithmically, the system maintains the flexibility of manual scheduling while eliminating the labor intensity. The scheduler processes multiple constraints and generates optimized schedules automatically, changing the labor requirement parameter from high manual effort to minimal automated processing
3Adaptability or versatility
If manual coordination is used to schedule network changes, then adaptability to constraints is maintained, but conflict resolution accuracy decreases
Solution Approach 1:
The automated scheduler implements feedback mechanisms that continuously monitor change requests, detect conflicts, and adjust schedules accordingly. The system receives feedback from network functions about their constraints and preferred timing, processes this information through automated algorithms, and generates schedules that resolve conflicts accurately. This feedback loop maintains adaptability to diverse constraints while improving conflict resolution accuracy through systematic automated analysis
Solution Approach 2:
The system performs preliminary actions by requiring network functions to declare their change requirements, constraints, and preferred timing in advance. The automated scheduler processes these pre-declared information and proactively resolves conflicts before they occur, rather than reacting to conflicts as they arise. This preliminary declaration and processing approach maintains adaptability to constraints while significantly improving conflict resolution accuracy through systematic pre-analysis
4Loss of time
If automated scheduling is implemented, then time consumption and error rate are reduced, but system complexity increases
Solution Approach 1:
The automated scheduling system is segmented into distinct functional modules: change declaration modules for each network function, a central automated scheduler, and schedule generation modules. Each module handles specific tasks independently - declaring constraints, processing conflicts, and generating schedules. This segmentation reduces overall system complexity by dividing the complex scheduling problem into manageable, independent components that can be processed systematically
Solution Approach 2:
The automated scheduler serves multiple functions within a single system: it processes change requests, resolves temporal conflicts, resolves resource conflicts, generates optimized schedules, and communicates with network functions. By making the scheduler multi-functional, the system reduces the need for separate specialized systems, thereby reducing overall complexity while achieving automated scheduling benefits
Data Source
AI summary
A new scalable approach to conflict-free deployment of changes across networks. The conflict rules or constraints may be modeled using policies and algorithms to determine an optimized schedule for change deployment.