Network Upgrade Scheduling via Traffic Analysis
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Solution Overview
Problem
Network upgrades often interrupt network performance, causing connectivity issues and productivity losses due to reliance on assumptions about optimal upgrade times rather than data-driven approaches.
Innovation Solution
An upgrade manager analyzes historical data traffic patterns to identify non-overlapping time windows with minimal data traffic, selecting the best time for upgrades based on actual network conditions to minimize disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network upgrades are applied to improve performance, reliability, and security, then network quality is improved, but network performance is interrupted
Solution Approach 1:
The system performs preliminary analysis of historical data traffic patterns before scheduling upgrades. By examining past traffic data and identifying optimal time windows in advance, the system prepares upgrade schedules that minimize disruption to network performance while ensuring upgrades are applied to improve reliability.
2Ease of operation
If network upgrades are scheduled based on assumptions about optimal times, then upgrade implementation is simplified, but actual network disruption is increased
Solution Approach 1:
The system uses feedback from historical data traffic analysis to dynamically determine optimal upgrade time windows. By continuously monitoring and analyzing actual network traffic patterns, the system adjusts upgrade schedules based on real evidence rather than assumptions, reducing disruption to client sessions while maintaining ease of operation through automated scheduling.
3Productivity
If network upgrades are applied during high-traffic periods to maintain service availability, then client accessibility is improved, but upgrade success and network stability are reduced
Solution Approach 1:
The system performs preliminary analysis of historical data traffic patterns to identify time windows with minimal data traffic before scheduling upgrades. This advance preparation allows the system to select optimal upgrade times that balance client accessibility with upgrade success probability, avoiding both high-traffic and extremely low-traffic periods.
Data Source
AI summary
An example of a system may include a processing resource and a computing device comprising instructions executable by the processing resource to determine an interval based on an amount of time to upgrade a network; determine a series of time windows based on the interval; analyze data traffic in the network over the series of time windows; identify a subset of the series of time windows that are sequential and non-overlapping; and select a particular time window from the subset of the series of time windows to perform an upgrade of the network based on the analyzed data traffic.