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Docker self-adaptive scheduling system with task sensing function

A scheduling system and self-adaptive technology, applied in the field of cloud computing, can solve problems such as sudden loads that cannot be solved, and achieve the effect of improving prediction accuracy and effectiveness

Inactive Publication Date: 2018-06-29
SHANGHAI DIANJI UNIV
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AI Technical Summary

Problems solved by technology

[0010] However, none of the above-mentioned technical solutions can solve the problem of the burst load proposed by the present invention

Method used

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  • Docker self-adaptive scheduling system with task sensing function
  • Docker self-adaptive scheduling system with task sensing function
  • Docker self-adaptive scheduling system with task sensing function

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Embodiment Construction

[0033] The overall framework and process of the task-aware Docker adaptive scheduling method of the present invention are shown in the accompanying drawings figure 1 As shown, this method builds a task-aware model based on parameters such as the resource usage rate and load of each microservice, uses the adaptive Kalman filter to predict the service response time, and adjusts the prediction model in real time through fuzzy logic. Whether the service quality is breached is used as the container scheduling standard to achieve the purpose of resource elastic supply.

[0034] The process flow of the task-aware Docker adaptive scheduling method of the present invention can be described as:

[0035] ① The data collector collects the load of each container and the utilization rate of system resources such as CPU and memory;

[0036] ②Based on queuing theory, the performance modeler uses the resource usage rate in step ① as a benchmark to build an application performance model and de...

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Abstract

Disclosed is a Docker self-adaptive scheduling system with a task sensing function. A Docker self-adaptive scheduling method comprises the steps that a data collector collects the load of each container and the resource usage rate of a CPU and a memory system; based on a queuing theory and with the resource usage rate as a benchmark, a performance modeler constructs an application performance model and characterizes an association relationship of the load and response time; a response time predictor estimates parameters of the performance model during running through a Kalman filter, wherein estimation is conducted under a convergence condition of meeting a predicted and measured response error expectation; a feed-forward controller analyzes a residual mean and variance through a fuzzy controller to obtain a feed-forward adjustment value of a control parameter of the Kalman filter; a container scheduler judges whether or not a predicted value of the response time violates application service quality and conducts scheduling according to a scheduling algorithm; the container scheduler conducts container expansion or shrinkage or migration.

Description

technical field [0001] The invention belongs to the technical field of cloud computing, and in particular relates to a task-aware Docker adaptive scheduling system under a micro-service architecture. Background technique [0002] The microservice architecture embodies the design idea of ​​Internet applications. Its core concepts are fine-grained module division, service interface encapsulation, and lightweight communication interaction. Microservice itself has good scalability and is gradually becoming the mainstream architecture model for constructing Internet applications. , but from the perspective of operation and maintenance, it is still a challenge to deal with typical sudden Internet load scenarios and ensure application service quality. [0003] In recent years, lightweight container technology has emerged as the times require. As a logical abstraction of physical resources, containers have the characteristics of less resource occupation and fast resource supply. The...

Claims

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Application Information

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IPC IPC(8): G06F9/50G06F9/48
CPCG06F9/4881G06F9/5027
Inventor 杨志和
Owner SHANGHAI DIANJI UNIV
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