Network Traffic Statistics Collection via Dynamic Message Group Context Switching
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Solution Overview
Problem
Conventional network traffic statistics collection systems face inefficiencies due to limited resources, requiring significant memory and processing power, and are cumbersome when switching between multiple message group contexts, leading to prolonged testing periods and resource constraints.
Innovation Solution
Implementing a system that generates and uses test messages with multiple context-specific message group identifiers (MGIDs) to enable efficient switching between active message group contexts during testing, allowing for continuous network traffic statistics collection without interrupting test message transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple message group contexts are tested using conventional systems, then comprehensive statistics can be gathered, but test reconfiguration and restarts are required which are cumbersome and inefficient
Solution Approach 1:
The system dynamically switches between multiple message group contexts during a single continuous test by processing different MGIDs in test messages according to different contexts. The test system maintains multiple context configurations and activates them dynamically based on the MGID present in each test message, eliminating the need for static reconfiguration between tests.
Solution Approach 2:
The test system is designed to handle multiple message group contexts simultaneously within a single test framework. By incorporating multiple MGID fields in test messages and maintaining multiple context configurations, the system performs the function of testing different message groups without requiring separate test executions, thereby achieving multi-functionality.
2Adaptability or versatility
If the number of MGIDs increases to cover more message groups, then more comprehensive statistics are collected, but the size of the statistics table and processing requirements increase
Solution Approach 1:
The system segments the statistics collection by maintaining separate context configurations for different message groups. Each message group context has its own configuration parameters and statistics tracking, allowing the system to handle large numbers of MGIDs by organizing them into manageable contextual segments rather than a single monolithic table.
Solution Approach 2:
Different context configurations are applied locally to different MGIDs based on their specific requirements. Each message group context can have customized parameters, filters, and statistics tracking tailored to its specific needs, rather than using a uniform approach for all MGIDs. This reduces overall complexity by optimizing each segment independently.
3Productivity
If continuous testing is performed without interruptions, then testing efficiency is improved, but resource constraints on receive ports limit the ability to handle multiple contexts
Solution Approach 1:
The system implements partial action by having the receive port process only the necessary portions of test messages relevant to the current active context. By selectively processing messages based on MGID matching and context activation, the system avoids the need for full resource allocation for all possible contexts simultaneously, enabling continuous testing within resource constraints.
Data Source
AI summary
Methods, systems, and computer readable media for network traffic statistics collection are disclosed. One method for network traffic statistics collection includes during testing of a system under test (SUT): receiving a first trigger message indicating a first message group context for statistics collection; receiving, from the SUT, a first test message of a plurality of test messages, wherein the first test message includes a first message group identifier (MGID) and a second MGID, wherein the first MGID is associated with the first message group context and the second MGID is associated with a second message group context; and performing, using the first MGID, statistics collection associated with the first message group context. The method may also include changing from the first message group context to the second message group context during the test and using the second message group context for statistics collection.


