Endpoint Pair Selection for Network Testing
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Solution Overview
Problem
Existing network testing methods face inefficiencies in selecting connectable endpoint pairs for performance testing, as the large number of candidate pairs requires significant time to search through, and prior knowledge optimization is needed to reduce this time.
Innovation Solution
A process involving ranking endpoint pairs based on stored connectivity data, checking connectivity by message exchange, and optimizing the search by dividing pairs into batches for concurrent checking, ensures efficient selection of connectable pairs for network testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large number of candidate endpoint pairs are searched through to ensure finding connectable pairs for network testing, then the reliability of test execution is improved, but the time required to locate suitable pairs increases significantly
Solution Approach 1:
The system performs preliminary actions by maintaining stored connectivity data about endpoint pairs that have been previously tested and found to be connectable. When a new network test is requested, the system first queries this stored data to identify candidate endpoint pairs that are likely to be connectable, rather than searching through all possible pairs from scratch. This preliminary filtering based on historical connectivity information significantly reduces the search space while maintaining high reliability in finding suitable test pairs.
2Device complexity
If connectivity checking is performed sequentially for each endpoint pair, then the complexity of the checking process is reduced, but the productivity of locating connectable pairs decreases
Solution Approach 1:
The system segments the connectivity checking process by dividing candidate endpoint pairs into multiple batches. Each batch is checked for connectivity in parallel using multiple threads or processes. This segmentation transforms a single sequential checking process into multiple concurrent operations, significantly improving productivity in locating connectable pairs while keeping individual batch checking relatively simple.
Solution Approach 2:
The system dynamically adjusts the checking process by using stored connectivity data to prioritize and filter candidate endpoint pairs before batching them for parallel checking. The batching and parallel execution are dynamically configured based on the number of candidates and available resources, optimizing the balance between complexity and productivity for different test scenarios.
Data Source
AI summary
Methods and apparatus for conducting a test of a network including a plurality of endpoints, each endpoint including a software agent for conducting network tests. Candidate endpoints pairs to conduct the test may be identified from the plurality of endpoints. The candidate endpoints pairs may be ranked in accordance with stored connectivity data. The connectivity of the candidate endpoint pairs may be checked in rank order until a connectable endpoint pair is located. The connectable endpoint pair may be instructed to conduct the test.