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Workflow execution optimization method based on distributed estimation algorithm in cloud computing environment

A cloud computing environment, distributed estimation technology, applied in the field of information technology, system engineering, and computer technology, can solve the problems of lack of integrated collaborative optimization methods for resource allocation and task scheduling, and low execution performance of cloud workflows

Inactive Publication Date: 2020-04-17
ZHEJIANG GONGSHANG UNIVERSITY
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Problems solved by technology

[0005] Aiming at the current optimization of cloud workflow execution, usually only from the perspective of resource configuration or task scheduling, the lack of an integrated collaborative optimization method for resource configuration and task scheduling, and the low performance of cloud workflow execution, the present invention provides a cloud computing The workflow execution optimization method based on the distributed estimation algorithm in the environment effectively improves the performance of cloud workflow execution

Method used

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  • Workflow execution optimization method based on distributed estimation algorithm in cloud computing environment
  • Workflow execution optimization method based on distributed estimation algorithm in cloud computing environment
  • Workflow execution optimization method based on distributed estimation algorithm in cloud computing environment

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Embodiment Construction

[0183] Combine below figure 1 , figure 2 The present invention will be further described in detail with reference to and examples, but the present invention is not limited to the following examples.

[0184] Assume that the cloud computing service provider, that is, the cloud computing environment, has five virtual machine types vm numbered from 1 to 5 1 , vm 2 , vm 3 , vm 4 , vm 5 Available for lease, the computing power, bandwidth, unit time cost, fixed start-up cost, minimum billing time unit, and minimum start-up time of various virtual machine types are shown in Table 1; the timing relationship between a Montage workflow task is as follows figure 2 As shown, there are 15 tasks numbered from 1 to 15 t 1 , t 2 ,...,t 15 The composition, the execution length of each task, the name and length of the input files required for processing and the processed output files are shown in Table 2.

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[0186] Table 1

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[0189] Table 2

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Abstract

The invention discloses a workflow execution optimization method based on a distributed estimation algorithm in a cloud computing environment. The workflow execution optimization method comprises thefollowing steps: acquiring information required by execution optimization; calculating a hierarchical value of the task; initializing a contemporary population; decoding the improved contemporary population, calculating the fitness value of the improved contemporary population, and carrying out optimal individual storage; constructing an elitist population, updating a probability model, sampling the probability model to generate a new contemporary population, and outputting an optimization result until a termination condition is met. Compared with a traditional method, the method has the advantages that topological sorting and continuous biased coding, initial individual generation based on hierarchy and benefit ratio, serial individual decoding based on an insertion mode, individual improvement based on forward and backward and new individual generation based on sampling are adopted; and the optimization capability and the search efficiency of the algorithm are improved through methods and strategies such as optimal individual storage.

Description

technical field [0001] The present invention relates to the fields of computer technology, information technology and system engineering, in particular to a cloud workflow execution optimization method, more specifically, to a workflow execution optimization method based on a distributed estimation algorithm in a cloud computing environment. Background technique [0002] Workflow under the cloud computing environment, referred to as "cloud workflow", is the integration of cloud computing and workflow-related technologies. Management, supply chain management and health care and other fields have broad application prospects. In cloud workflow, there are various types of computing resources and multiple tasks, and there are timing constraints between tasks. During execution, virtual machines are usually used as the smallest allocation unit of computing resources to receive and process these tasks. Cloud workflow execution or scheduling optimization refers to how to reasonably ...

Claims

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Application Information

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IPC IPC(8): G06F9/48G06F9/455
CPCG06F9/45558G06F9/4881G06F2009/4557
Inventor 谢毅桂奉献孙鹤
Owner ZHEJIANG GONGSHANG UNIVERSITY
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