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An Adaptive Heartbeat Detection Method Based on Time Series Prediction

A heartbeat detection and time series technology, applied in transmission systems, electrical components, etc., can solve the problems that traditional methods cannot adapt to dynamic changes and are prone to heartbeat misjudgments, and achieve accurate heartbeat cycle and accurate heartbeat cycle prediction value.

Active Publication Date: 2022-02-11
BEIJING INST OF COMP TECH & APPL
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Problems solved by technology

In a high-availability cluster system, the load of each node and the communication network between nodes change dynamically, the traditional method cannot adapt to its dynamic change characteristics, and heartbeat misjudgment is prone to occur

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  • An Adaptive Heartbeat Detection Method Based on Time Series Prediction
  • An Adaptive Heartbeat Detection Method Based on Time Series Prediction
  • An Adaptive Heartbeat Detection Method Based on Time Series Prediction

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Embodiment Construction

[0036] In order to make the purpose, content, and advantages of the present invention clearer, the specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0037] The invention proposes an adaptive heartbeat detection method based on time series prediction aiming at the time series characteristics of cluster node load changes.

[0038] like figure 1 As shown, {..., ST i-2 , ST i-1 , ST i , ST i+1 ,...} is the heartbeat information between the monitored node and the monitoring node, {..., n i-2 , n i-1 , n i , n i+1 , ...} is the network delay between the monitored node and the monitoring node.

[0039] Dinda P.A. found that the load change of nodes is a time series through long-term tracking and observation of servers. The heartbeat sending period of the monitored node is a function of the monitored node load (CPU, memory, hard disk, etc.), so the heartbeat sendi...

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Abstract

The invention relates to an adaptive heartbeat detection method based on time series prediction, and belongs to the technical field of high reliability computing. In the present invention, the heartbeat sending cycle ΔST of the monitored node and the monitoring node i and the heartbeat receiving period ΔHT i All are variable parameters, which can be adaptively adjusted according to the load of each node in the high-availability cluster and the network conditions between nodes, and the heartbeat cycle is more accurate; the heartbeat detection adopts the method of combining push model and pull model, and the normal state The monitored node periodically sends heartbeat information to the monitoring node; when the monitoring node does not receive the heartbeat information of the monitored node within the specified timeout period, it actively sends an inquiry signal, and the heartbeat receiving timeout time is also adaptively adjusted; The heartbeat sending cycle and the heartbeat receiving cycle are modeled based on time series ARMA, and the heartbeat sending cycle and the heartbeat receiving cycle are predicted by one step forward. Compared with the moving average method, the predicted value of the heartbeat cycle is more accurate.

Description

technical field [0001] The invention belongs to the technical field of high reliability computing, and in particular relates to an adaptive heartbeat detection method based on time series prediction. Background technique [0002] The heartbeat mechanism is the basis of high-availability clusters. At present, the commonly used heartbeat detection methods in high-availability clusters mainly include push model, pull model, dual model, chat type error detection, hierarchical type error detection, etc., but these methods use fixed heartbeat cycle. In a high-availability cluster system, the load of each node and the communication network between nodes change dynamically, the traditional method cannot adapt to its dynamic change characteristics, and heartbeat misjudgment is prone to occur. Wu Shuhua and others proposed a highly reliable heartbeat protocol for the Galaxy Kylin operating system. Through the improvement of the traditional push model, variable heartbeat time interval...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L43/10H04L67/10
CPCH04L43/10H04L67/10
Inventor 刘宗宝张力李之乾张琨李勇翔
Owner BEIJING INST OF COMP TECH & APPL
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