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Cloud computing resource scheduling algorithm based on Naive Bayesian

A resource scheduling and cloud computing technology, applied in computing, program control design, program startup/switching, etc., can solve problems such as high time complexity and cumbersome operation, and achieve low time complexity, solve cumbersome operation, and simple operation. Effect

Inactive Publication Date: 2019-01-08
HARBIN UNIV OF SCI & TECH
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Problems solved by technology

[0004] In order to realize the use of lower time complexity and solve the problems of cumbersome operation and high time complexity of traditional scheduling algorithms, a cloud computing resource scheduling algorithm based on naive Bayesian is designed.

Method used

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  • Cloud computing resource scheduling algorithm based on Naive Bayesian
  • Cloud computing resource scheduling algorithm based on Naive Bayesian
  • Cloud computing resource scheduling algorithm based on Naive Bayesian

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Embodiment Construction

[0030] A cloud computing resource scheduling algorithm based on Naive Bayesian, its steps are:

[0031] Step 1: Use the HEFT scheduling algorithm to schedule tasks composed of randomly generated directed acyclic graphs and processing times on different CPUs, and obtain scheduling results. as attached figure 1 And attached figure 2 As shown, a directed acyclic graph of tasks to be scheduled in cloud computing and their processing time on different CPUs. There are 10 tasks in the figure, which can be processed on 3 different CPUs. figure 1 The nodes in the middle represent the task numbers; the arrows between the connecting nodes represent the mutual sequence constraints between the tasks, and the positions of the first and last arrows indicate the sequence of task processing, that is, the tasks at the end of the arrows must be completed before they can be processed again. To process the task pointed by the arrow; the number on the side between the connecting node and the nod...

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Abstract

The invention relates to a cloud computing resource scheduling algorithm based on Naive Bayesian. The algorithm includes: utilizing an HEFT algorithm to schedule tasks composed of directed acyclic graph and processing time on different CPUs to obtain scheduling results; taking the scheduling result, constructing a training set D needed by machine learning, taking the processing time and the Rank value of a single task on all CPUs as the attributes of the training set D, taking a subtask in a directed acyclic graph to be scheduled, and calculating a priori probability and a conditional probability of dividing the subtask into different CPUs; using a naive Bayesian classifier in machine learning to predict the subtask scheduling result; when all the sub-task scheduling results are predictedto be completed, outputting the Gantt chart to complete the task scheduling. The invention solves the problems of tedious operation and high time complexity of the traditional algorithm, and has the advantages of simple operation and low time complexity.

Description

1. Technical field [0001] The invention relates to the technical field of cloud computing resource scheduling, and is a cloud computing resource scheduling algorithm based on naive Bayesian. 2. Background technology [0002] Resource scheduling is one of the important research directions in cloud computing. To solve the CPU resource scheduling problem in cloud computing, traditional scheduling algorithms can be used. For example, the HEFT scheduling algorithm mainly includes two steps: the first is to determine the priority of the task, that is, to calculate the priority of the task and sort it according to the priority; Scheduling to the appropriate CPU for processing. The task priority level is determined according to the Rank value, which represents the average computing cost and communication cost of the task on the CPU, and is arranged in descending order in the task table. The principle of CPU selection is to arrange the tasks that need to be scheduled on the proces...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/48
CPCG06F9/4881
Inventor 辛宇王亚迪
Owner HARBIN UNIV OF SCI & TECH
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