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Cloud workflow scheduling method based on collected discrete particle swarm optimization

A discrete particle swarm and scheduling method technology, applied in the field of cloud workflow scheduling optimization based on ensemble particle swarm algorithm, can solve problems such as knapsack problem

Inactive Publication Date: 2013-08-28
SUN YAT SEN UNIV
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Problems solved by technology

Although PSO is an algorithm that is very suitable for the optimization of continuous domain problems and has been quite successfully applied in many continuous space domains, there are still many practical problems that are defined in discrete spaces, such as typical discrete combination problems There are knapsack problems, traveling salesman problems, scheduling problems, etc.

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  • Cloud workflow scheduling method based on collected discrete particle swarm optimization
  • Cloud workflow scheduling method based on collected discrete particle swarm optimization
  • Cloud workflow scheduling method based on collected discrete particle swarm optimization

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Embodiment Construction

[0020] The method of the invention will be further described below in conjunction with the accompanying drawings.

[0021] A cloud workflow can be given in the form of a directed acyclic graph (DAG) G = (V, A). In this model, let n be the number of tasks in the workflow, the set of nodes V={T 1 ,T 2 ,...,T n} corresponds to a task in the workflow. The set A of arrows represents the priority relationship between tasks. Each task in the workflow can be realized by some cloud computing services in the cloud system, that is, each task T i (1≤i≤n) all have a set of cloud computing services that can perform the task in Indicates that the cloud is provided to the task T i A service instance of m i means T i The number of service instances available. For each service instance Consider three constraints, the cost execution time and reliability

[0022] In order to provide users with a QoS for elastically managing workflows in the cloud system, the cloud workflow sc...

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Abstract

The invention discloses a cloud workflow scheduling method based on collected discrete particle swarm optimization. Aiming at cloud workflow scheduling with different QoS requirements, the method adopts a novel collected discrete particle swarm optimization algorithm, through redefinition for the speed, the position and relative update operation of particle swarm optimization in collected space, application requirements for cloud workflow scheduling optimization in discrete space can be met, and efficiency of cloud workflow scheduling is improved.

Description

Technical field: [0001] The invention relates to two fields of cloud computing and intelligent computing, and mainly relates to a method for optimizing cloud workflow scheduling based on an aggregate particle swarm algorithm. technical background: [0002] As an emerging resource usage and delivery mode, cloud computing allows users to use various resources anytime and anywhere according to their needs, which has been gradually recognized by the academic and industrial circles. It provides a flexible way to implement a computationally intensive workflow application based on a delivery model. In cloud systems, as users pay more and more attention to the quality of service (QoS) satisfaction, the problem of dynamic scheduling of cloud workflows that meets user-defined requirements has gradually become an urgent and challenging problem to be solved. [0003] Particle Swarm Optimization (PSO) is a random search algorithm that simulates the predation of birds and fish in nature....

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06N3/00H04L29/08
Inventor 张军陈伟能刘宇彭浩林
Owner SUN YAT SEN UNIV
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