Network Resource Congestion Reduction via Predictive Item Transfer Scheduling
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Solution Overview
Problem
Current sourcing technologies for network resources often lead to network resource congestion due to overloading, resulting in delays and failures related to waiting or repeated availability inquiries.
Innovation Solution
A system that monitors network resources to assess current or predicted item availability, identifies nearby sources, and establishes non-overlapping time frames for item transfers to minimize congestion, by determining distances, modes of transfer, and prioritizing sources based on proximity, distance, and transfer efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If current sourcing technologies are used to obtain items from distributed sources, then the network resource can acquire necessary items, but the network resource becomes overloaded and congested
Solution Approach 1:
The system performs preliminary actions by monitoring network resource levels and predicting future availability before congestion occurs. It proactively schedules item transfers in advance during off-peak periods, preventing network overload before it happens rather than reacting after congestion occurs.
Solution Approach 2:
The system implements periodic monitoring of network resource levels and schedules item transfers at periodic intervals during predicted low-utilization periods. This periodic action distributes transfer loads evenly over time, preventing continuous network congestion while ensuring adequate item supply.
2Productivity
If multiple sources transfer items simultaneously to meet demand, then the network resource receives sufficient items, but delays and failures occur due to network congestion
Solution Approach 1:
The system segments the item transfer process by dividing it into multiple discrete transfer operations scheduled at different time periods. Instead of one large simultaneous transfer that causes congestion, the total item quantity is split into smaller batches transferred sequentially during low-utilization periods, improving overall transfer efficiency while minimizing delays.
Solution Approach 2:
The system dynamically adjusts transfer schedules based on real-time network utilization patterns. Transfer timing is flexible and adapts to changing network conditions, selecting optimal moments when network load is lowest. This dynamic scheduling maximizes transfer efficiency while minimizing delays caused by congestion.
3Reliability
If frequent availability inquiries are made to ensure item supply, then the network resource can maintain adequate stock, but repeated inquiries cause additional network congestion
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring network resource levels and using this information to predict future availability. This feedback loop allows the system to make informed decisions about transfer timing, reducing the need for frequent availability inquiries while maintaining reliable stock levels through predictive analytics.
Solution Approach 2:
The system performs preliminary availability assessments by monitoring trends and predicting future item levels before depletion occurs. This preliminary action reduces the need for frequent reactive inquiries, as the system can proactively schedule transfers based on predictions, thereby maintaining reliability while minimizing inquiry-related congestion.
Data Source
AI summary
In certain embodiments, a current amount of an item available from a network resource may be monitored. Based on the monitoring indicating that the current amount fails to satisfy a first threshold, one or more sources may be identified. The one or more sources may be within a threshold proximity of the network resource, and distances between the one or more sources and the network resource may be determined. One or more requests for the amounts of the item to be transferred from the one or more sources to the network resource within time frames may be generated. For example, the time frames may be based on the distances. The one or more requests may be transmitted to the one or more sources.