Server Data Source Ranking via Periodic Test Messages
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Solution Overview
Problem
Existing systems for ranking external data sources struggle to dynamically adjust rankings based on service levels, leading to suboptimal content presentation to users, as they do not effectively monitor and respond to changes in data source performance.
Innovation Solution
A server system that periodically sends test messages to data sources, monitors response times, and adjusts rankings in a ranking table based on service levels, including intermittent recovery messages with varying time delays to ensure optimal data source selection and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the server sends test messages periodically to monitor data source performance, then the reliability of content retrieval is improved, but the loss of time for monitoring and processing increases
Solution Approach 1:
The server implements periodic monitoring by sending test messages at predetermined intervals to data sources. This periodic action allows the system to balance between maintaining up-to-date performance information (improving reliability) and avoiding excessive monitoring frequency (reducing time loss). The interval between test messages can be adjusted based on service level requirements and data source performance patterns.
2Manufacturing precision
If the server adjusts rankings dynamically based on service levels, then the quality of content presentation is improved, but the device complexity increases
Solution Approach 1:
The server implements dynamic ranking adjustment where data source rankings in the ranking table are automatically updated based on real-time service level performance. Instead of static rankings, the system continuously adapts the ranking order based on measured performance metrics, allowing the highest quality content sources to be prioritized while managing complexity through automated algorithms.
Solution Approach 2:
The system establishes a feedback loop where test message responses are analyzed to determine service level compliance, and this information feeds back into automatic ranking adjustments. The server monitors response times and performance metrics, compares them against service level agreements, and automatically modifies the ranking table accordingly, improving content quality while reducing manual intervention complexity.
3Reliability
If the server blocks failing data sources, then the reliability of content retrieval is improved, but the productivity of the system decreases
Solution Approach 1:
The server implements a block and recover mechanism where data sources that fail to meet service levels are temporarily blocked from the ranking table to maintain reliability. However, the system periodically attempts to recover blocked data sources by sending test messages and evaluating whether they have returned to acceptable performance levels. Once recovered, data sources are reinstated to the ranking table, balancing reliability with productivity by preventing permanent loss of potentially useful data sources.
Data Source
AI summary
A server, method, and non-transitory computer readable medium for ranking a plurality of data sources are provided. The server includes a network interface, a memory storage unit and a processor. The method involves sending a test message, monitoring an external network for a response to the test message, determining whether a service level is satisfied and adjusting the rank of the data source. The non-transitory computer readable medium is encoded with programming instructions to direct a processor to carry out the method.