Method and system for cooperative adaptive adjustment of detection period

Abstract

The invention discloses a detection period cooperative adaptive adjustment method and system, and the method comprises the following steps: building a prediction model of path change; establishing a linear relationship between the path attribute prediction value of the prediction model and the optimal detection period through a linear regression method; when the system runs, carrying out self-adaptive adjustment of a detection period according to a preset period, which comprises the following steps: predicting all path attributes to obtain predicted values of all paths; and processing predicted values and detection budget of all paths through a linear relationship to obtain detection period adjustment values of all paths. According to the method, the detection period can be adjusted according to the weighing preference of an administrator, the method is suitable for measurement of detection path changes, detection period parameters of multiple paths are dynamically adjusted according to actual path change characteristics, and reasonable deployment of detection resources is achieved.

Description

technical field [0001] The invention relates to the technical field of computer network measurement, in particular to a detection cycle cooperative self-adaptive adjustment method and system. Background technique [0002] Network measurement is to collect data on network operating parameters and indicators through a series of hardware devices and software programs, and then mine and analyze the characteristics of the collected data. Through analysis, the problems existing in the network can be obtained. Traffic balance, network routing strategy and algorithm research are all of great significance. Due to the temporal and spatial differences of network behavior, the uncontrollability of network processes, and the non-reproducibility of network behavior, continuous measurement on a global scale is of great significance. [0003] Global continuous network measurement is an important means for high-performance protocol design, network planning and construction, and network faul...

AI Technical Summary

Problems solved by technology

[0005] However, conventional measurement systems probe each path on average

This single fixed probing method has significant limitations

Probes have limited probing capabilities due to source link capacity, CPU utilization, and probing budget constraints, which prevent them from frequently tracing paths to observe changes in all paths

Moreover, the interval of network path changes is variable, some routes are stable, and some routes change frequently

Probing all paths with the same frequency will waste probing resources on stable paths and miss changes on frequently changing paths

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