Handle recognition system analysis load balancing method based on neural network

A neural network and load balancing technology, which is applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as short response time, high load prediction accuracy, and high cluster utilization, so as to improve prediction accuracy, The effect of improving cluster utilization and improving the efficiency of processing tasks

Pending Publication Date: 2021-12-10
码客工场工业科技北京有限公司
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Problems solved by technology

Existing dynamic load balancing algorithms cannot satisfy short response time, high load prediction accuracy and high cluster utilization at the same time

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  • Handle recognition system analysis load balancing method based on neural network
  • Handle recognition system analysis load balancing method based on neural network
  • Handle recognition system analysis load balancing method based on neural network

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Embodiment Construction

[0046] The present invention will be described in detail through specific embodiments below in conjunction with the accompanying drawings, but it does not constitute a limitation to the present invention.

[0047] A neural network-based Handle identification system analysis load balancing method, including: establishing an enterprise-server mapping table, recording time series data, training and generating a load utilization prediction model and task volume prediction, and updating the enterprise-server mapping table according to the prediction results. Specific as figure 1 As shown, this example is divided into three parts, which are initialization phase, periodic update phase and operation phase.

[0048] 1. Initialization stage: including steps (1) to (3)

[0049] (1) First use the enterprise prefixes that have been registered at the secondary node, and establish mappings with the servers in sequence according to the numbering order of the prefixes, and generate a many-to-...

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Abstract

The invention discloses a Handle recognition system analysis load balancing method based on a neural network. The method comprises the steps of establishing an enterprise-server mapping table, recording time sequence data, training and generating a load utilization rate prediction model and task load prediction, and updating the enterprise-server mapping table according to a prediction result. According to the invention, firstly, the enterprise-server mapping table is established to accelerate the task response speed and improve the task processing efficiency, the time sequence data and the BP neural network are used to generate the load utilization rate prediction model and improve the prediction accuracy, then the task quantity is predicted through the Elman neural network. the task quantity is input into a load utilization rate prediction model to estimate the load change of each server, and finally, a load utilization rate piecewise function and a strategy of dynamically modifying a mapping table are combined, so that the server cluster can well cope with the Handle recognition system analysis task, the utilization rate and the load balance degree of the server cluster are improved, and the time for executing the task is shortened.

Description

technical field [0001] The invention belongs to the technical field of load balancing and relates to a neural network method, in particular to a neural network-based load balancing method capable of predicting load changes of secondary node resolution servers. Background technique [0002] At present, the market scale of my country's industrial Internet is gradually expanding, and it is expected to reach the trillion level. The industrial Internet logo also undergoes explosive growth accordingly. Secondary node resolution servers often receive a large number of concurrent registration and query requests in a short period of time. Therefore, How to reasonably allocate the tasks of cluster servers and meet the maximum service demand is a key technical problem to be solved, and load balancing is one of the core technologies to solve the difficulties of server clusters. [0003] At present, load balancing algorithms are mainly divided into two categories: static load balancing al...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50G06N3/04G06N3/08
CPCG06F9/505G06N3/084G06N3/044G06N3/045
Inventor 张晓白宏钢
Owner 码客工场工业科技北京有限公司
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