Automated Access Point Upgrade Scheduling
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Solution Overview
Problem
Current manual scheduling of access point device upgrades in communication networks leads to significant service disruptions, prolonged upgrade times, and high operational costs due to the need for manual health checks, conflict resolution, and simultaneous execution of upgrades, which can result in coverage holes and congestion.
Innovation Solution
An automated scheduling system that uses service history data, policy data, and upgrade data to determine an optimized upgrade schedule, minimizing service disruptions and reducing operational costs by strategically selecting AP devices for upgrades while ensuring continuous coverage and no congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual scheduling is used for access point device upgrades, then operational control is maintained, but service disruptions increase and upgrade completion time extends
Solution Approach 1:
The system enables self-service automation where the scheduling mechanism automatically performs health checks, detects conflicts, and executes upgrade scheduling without manual intervention. The automated system analyzes service history data, policy data, and upgrade data to generate optimized schedules, eliminating the need for manual operational control while significantly reducing upgrade completion time across the network.
Solution Approach 2:
The patent replaces the mechanical manual scheduling process with an automated computational system. Instead of manual health checks and conflict resolution, the system uses automated algorithms that process service history data, policy data, and upgrade data to determine optimal upgrade schedules, thereby substituting human operational control with automated mechanical processes that achieve faster results.
2Productivity
If multiple AP devices are upgraded simultaneously to reduce total upgrade time, then productivity increases, but service disruptions worsen due to coverage holes and congestion
Solution Approach 1:
The system applies partial action by selectively upgrading only those AP devices that can be upgraded without causing service disruptions. The automated scheduling mechanism identifies subsets of AP devices whose upgrades will not create coverage holes or congestion, allowing parallel upgrades of multiple devices while maintaining service reliability. This partial upgrading approach enables higher throughput compared to sequential upgrades without sacrificing service continuity.
Solution Approach 2:
The system uses feedback from health checks and service history data to dynamically adjust upgrade scheduling decisions. By continuously monitoring network conditions and AP device health status, the automated system can determine which AP devices are safe to upgrade simultaneously without causing service disruptions. This feedback mechanism enables the system to maximize parallel upgrade operations while maintaining service reliability.
3Reliability
If manual health checks and conflict resolution are performed, then service reliability is maintained, but operational costs and time consumption increase
Solution Approach 1:
The system performs preliminary automated health checks and conflict detection before upgrade scheduling. By proactively analyzing service history data and identifying potential conflicts in advance, the system eliminates the need for time-consuming manual health checks during the upgrade process. This preliminary automated assessment maintains service reliability while significantly reducing operational time and costs.
Solution Approach 2:
The automated scheduling system performs self-service health checks and conflict resolution without requiring manual operational intervention. The system automatically monitors AP device health status, detects potential conflicts in upgrade schedules, and adjusts scheduling decisions accordingly, thereby maintaining service reliability while eliminating the time and costs associated with manual operational processes.
4Reliability
If upgrades are scheduled during off-peak hours to minimize service impact, then service disruptions are reduced, but upgrade completion time extends due to limited available windows
Solution Approach 1:
The system applies partial action by identifying and upgrading only those AP devices that can be safely upgraded during off-peak hours without causing service disruptions. The automated scheduling mechanism analyzes service history data to determine which AP devices have low traffic impact during off-peak periods, allowing parallel upgrades of multiple devices within available windows. This approach maximizes the use of off-peak hours while maintaining service reliability, thereby reducing total upgrade duration compared to sequential upgrades.
Solution Approach 2:
The system dynamically adjusts upgrade scheduling based on real-time network conditions and traffic patterns. By continuously monitoring service history data and policy data, the automated system can flexibly identify off-peak hours and available upgrade windows, adapting the upgrade schedule to maximize utilization of these periods while minimizing service impact. This dynamic approach enables faster completion compared to static scheduling methods.
Data Source
AI summary
Communication networks go through frequent upgrades, whereby access point (AP) devices that serve network client devices are brought offline to effectuate the upgrade. Concurrently upgrading too many AP devices within a given geographic area can lead to coverage holes where no service is available, congestion where data cannot be sufficiently communicated, or other service degradation. On the other hand, upgrading too few AP devices within the area can result in a network-wide upgrade time that is too great. An architecture is presented that can efficiently generate a schedule for upgrading AP devices of a communication network.