Communications Link Exhaustion Forecasting
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Solution Overview
Problem
Current technologies lack effective methods for early detection and monitoring of communications link exhaustion, leading to costly replacements, service interruptions, and inefficient data flow management.
Innovation Solution
A method and graphical user interface (GUI) for monitoring and forecasting communications link exhaustion by calculating average and rate of change in utilization statistics, providing a graphical representation of data flow, and enabling users to navigate and sort communications links for timely replacements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If no monitoring system is implemented for communications links, then device complexity is reduced, but reliability deteriorates due to inability to detect exhaustion early
Solution Approach 1:
The communications link monitoring system automatically polls utilization statistics from network elements and performs exhaustion calculations without requiring manual intervention. The system self-manages the collection, storage, and analysis of utilization data, calculating average rates of change and forecasting exhaustion dates autonomously, thereby improving reliability while minimizing operational complexity.
Solution Approach 2:
The system continuously polls utilization statistics from communications links and feeds this data back into the monitoring database. By comparing current utilization against historical data and calculated average rates of change, the system provides feedback that enables early detection of exhaustion trends, allowing proactive replacement before actual failure occurs.
2Measurement precision
If utilization statistics are collected and analyzed continuously, then measurement precision improves for exhaustion detection, but use of energy increases due to continuous monitoring
Solution Approach 1:
The monitoring system polls utilization statistics at predetermined time intervals rather than continuously. This periodic sampling approach maintains measurement precision by capturing utilization trends over time while significantly reducing energy consumption compared to continuous monitoring. The system calculates average rates of change from these periodic samples to forecast exhaustion dates.
3Loss of time
If replacement is delayed until actual failure, then loss of time is reduced, but loss of substance increases due to emergency replacement costs
Solution Approach 1:
The system calculates forecasted exhaustion dates by analyzing utilization trends and average rates of change, enabling proactive scheduling of replacements before actual failure occurs. This preliminary action allows businesses to order replacement communications links in advance, avoiding emergency replacement costs and minimizing service interruption time by ensuring replacements are ready before exhaustion occurs.
Data Source
AI summary
A method, and graphical user interface are provided for monitoring the status and forecasting the exhaust date of communications links. Initially, data ports are monitored corresponding to one or more communications links over a period of time. Next, utilization statistics are polled and stored in a database. Thereafter, an average and a rate of change are calculated using the utilization statistics. Based on these calculations, a date of exhaustion can be forecasted. The user interface further provides a user the ability to monitor the status and select multiple communications links to ensure data is flowing properly.