Method, device and equipment for predicting service increment of content distribution network and medium

By analyzing the historical bandwidth data of the content distribution network, filtering and weighting the bandwidth data of the target historical cycle, the problem of inefficient manual evaluation of business increments in traditional methods is solved, and more efficient and accurate business increment prediction is achieved.

CN119814589AActive Publication Date: 2025-04-11CHINA TELECOM CLOUD TECH CO LTD
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Patent Information

Application Number
CN202411773091.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-04
Publication Date
2025-04-11
Estimated Expiration
2044-12-04

AI Technical Summary

Technical Problem

Traditional methods rely on manual collection of incremental information on customers' business, resulting in low efficiency and accuracy, making it difficult to accurately evaluate resource requirements for the next month.

Method used

By obtaining the bandwidth data of multiple historical cycles of the target service, selecting the most recent historical cycle as a reference, calculating its similarity with other historical cycles, filtering out the bandwidth data of the target historical cycle, and performing a weighted average to estimate the bandwidth data of the next cycle, thereby determining the target incremental information.

Benefits of technology

Improve the efficiency and accuracy of predicting the target incremental information of the next cycle, reduce manual intervention, save time and human resources.

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Abstract

The embodiment of the invention provides a service increment prediction method and device for a content distribution network, equipment and a medium. The method comprises the following steps: acquiring bandwidth data of a target service in a plurality of historical periods; selecting the bandwidth data of the latest historical period as reference bandwidth data according to the bandwidth data of the plurality of historical periods; determining the similarity between the reference bandwidth data and the bandwidth data of other historical periods except the reference bandwidth data; determining a preset number of bandwidth data of a target historical period according to the similarity; performing weighted average on the bandwidth data of the target historical period, and determining estimated bandwidth data of the next period; and determining target increment information of the next period according to the estimated bandwidth data of the next period. The bandwidth data of the target historical period is screened out by utilizing the bandwidth data of the plurality of historical periods, and the target increment information is determined according to the bandwidth data of the target historical period, so that the efficiency and accuracy of predicting the target increment information of the next period are improved.
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