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Method for constraining workflow scheduling in cloud environment based on ant colony optimization algorithm through deadline

An ant colony optimization algorithm and deadline technology, applied in computing, program startup/switching, program control design, etc., can solve problems such as inaccurate estimation of workflow deadlines

Inactive Publication Date: 2016-10-26
CENT SOUTH UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

Chen et al. proposed an ant colony optimization algorithm based on an adaptive heuristic model to solve the workflow scheduling problem, and achieved good results, but its application in the grid environment and the estimation of workflow deadlines are not accurate.

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  • Method for constraining workflow scheduling in cloud environment based on ant colony optimization algorithm through deadline
  • Method for constraining workflow scheduling in cloud environment based on ant colony optimization algorithm through deadline
  • Method for constraining workflow scheduling in cloud environment based on ant colony optimization algorithm through deadline

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Embodiment Construction

[0054] Below in conjunction with accompanying drawing, technical scheme of the present invention is described in detail:

[0055] Examples of cloud workflow applications using various cloud service models are shown in figure 1 As shown, because the cloud environment has a large number of resources, including computing resources, memory resources, storage resources and network resources, etc., and the resources can be dynamically expanded and used on demand, many enterprises and scientific research institutions submit various complex applications to the It can be implemented in different cloud environments, such as Software as a Service (Software as a Service, SaaS), Platform as a Service (PaaS, PaaS), and Infrastructure as a Service, IaaS (Infrastructure as a Service).

[0056] The architecture diagram of the cloud workflow management system is as follows: figure 2 As shown, the cloud workflow management system has four layers, from top to bottom are workflow application inp...

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Abstract

The invention discloses a method for constraining workflow scheduling in a cloud environment based on the ant colony optimization algorithm through deadline. The method comprises the steps: employing an ant colony system with a candidate list; respectively searching a workflow scheduling scheme in the cloud environment through a plurality of ants; carrying out the communication of a workflow scheduling result among the ants in a pheromone mode, thereby guiding the deciding of the subsequent search direction of ants and the workflow scheduling scheme. Compared with a conventional workflow scheduling method, the method can reduce the cost of the workflow scheduling in the cloud environment and improves the service quality for cloud users under the condition of meeting the deadline time QoS requirements of users.

Description

technical field [0001] The invention relates to a workflow scheduling method in a cloud environment, in particular to a deadline-constrained workflow scheduling method in a cloud environment based on an ant colony optimization algorithm. Background technique [0002] Cloud computing is an emerging way of providing resources at present. It provides all software and hardware resources as services to users and has the characteristics of paying on demand. Therefore, many enterprises and scientific research institutions submit various complex applications to different cloud environments. to execute. The workflow model is a common representation of applications, and the directed acyclic graph structure is a general modeling method for workflow models. One of the biggest problems in the cloud is workflow scheduling, such as QoS when meeting user deadlines. Under the requirement of minimizing the cost of workflow execution, common user QoS is the completion time and cost of workflo...

Claims

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Application Information

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IPC IPC(8): G06F9/48
CPCG06F9/4881G06F2209/484
Inventor 王勇黄春阳
Owner CENT SOUTH UNIV
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