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Multi-target task scheduling method and system

A task scheduling and multi-objective technology, applied in the field of multi-objective task scheduling methods and systems, can solve problems such as poor scheduling strategies, achieve the effect of improving resource utilization and achieving load balancing

Active Publication Date: 2019-11-22
CHANGSHA UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] A multi-objective task scheduling method and system provided by the present invention solves the technical problem that the scheduling strategy obtained by using the traditional task scheduling algorithm is not good

Method used

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  • Multi-target task scheduling method and system

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Experimental program
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Embodiment 1

[0064] refer to figure 1 , the multi-objective task scheduling method provided by Embodiment 1 of the present invention includes:

[0065] Step S101, use the fuzzy clustering algorithm to perform fuzzy clustering processing on tasks and virtual machines respectively, obtain a task cluster set and a virtual machine cluster set, and match the task cluster set with the virtual machine cluster set to obtain a matching set ;

[0066] Step S102, using the differential evolution algorithm to schedule the tasks in the matching set to the virtual machines in the matching set to obtain an initial scheduling result;

[0067] Step S103, according to the load value of the virtual machine in the initial scheduling result, the virtual machine is divided into a heavy load set, a balanced load set and a light load set;

[0068] Step S104, selecting a task set that needs to be rescheduled from the heavy load set to obtain a rescheduled task set;

[0069] Step S105, using the Q-value algorith...

Embodiment 2

[0121] refer to figure 2 , the multi-objective task scheduling method provided by Embodiment 2 of the present invention includes:

[0122] Step S201, use the fuzzy clustering algorithm to perform fuzzy clustering processing on tasks and virtual machines respectively, obtain a task cluster set and a virtual machine cluster set, and match the task cluster set with the virtual machine cluster set to obtain a matching set .

[0123] With the rapid development of cloud computing, the scale of resource clusters continues to expand. Task scheduling in the current cloud environment is often aimed at all resources, without considering the relationship between tasks and resources. When there are many resources and a large amount of tasks, the time spent on assigning tasks to appropriate resource nodes will increase, which directly It will have a greater impact on the final completion time of the task, and will also lead to a decrease in the efficiency of task execution. Considering ...

Embodiment 3

[0227] Such as Figure 9 As shown, the multi-objective task scheduling method of the third embodiment includes:

[0228] Step1: Use the fuzzy clustering algorithm to perform fuzzy clustering processing on independent tasks and virtual machines, and divide them into categories according to task characteristics and virtual machine characteristics;

[0229] Step2: Match between collections according to the resource requirements of task collections and the overall performance of virtual machine collections;

[0230] Step3: sequentially schedule the tasks in the set to the virtual machine resources in the corresponding virtual machine set according to the multi-objective task scheduling strategy of the improved differential evolution algorithm, and obtain the scheduling result of the initial task to the virtual machine;

[0231] Step4: Calculate the load status of the virtual machine, group the virtual machines according to the load value, and divide them into three groups: heavy ...

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Abstract

The invention discloses a multi-target task scheduling method and a multi-target task scheduling system. Fuzzy clustering processing is performed on a task and a virtual machine by using a fuzzy clustering algorithm; the obtained task clustering set is matched with the virtual machine clustering set; obtaining a matching set, differential evolution algorithm, scheduling the tasks in the matching set to the virtual machines in the matching set; obtaining initial scheduling results, according to the load value of the virtual machine in the initial scheduling result; dividing the virtual machinesinto a heavy load set, a balanced load set and a light load set; selecting a task set needing to be rescheduled from the heavy load set, obtaining a rescheduling task set and adopting a Q-value algorithm; tasks in a rescheduling task set are scheduled to virtual machines in a light load set, the technical problem that a scheduling strategy obtained through a traditional task scheduling algorithmis poor is solved, local resource tasks are reallocated through a Q-value method. The load balancing of global resources is achieved, and the resource utilization rate is increased.

Description

technical field [0001] The invention relates to the technical field of cloud computing, in particular to a multi-objective task scheduling method and system. Background technique [0002] Cloud computing is a market-oriented emerging technology based on network development, which has become a hot topic in academic research in recent years. As its market share increases year by year and resource scale expands, a huge number of users and tasks follow, which makes it more difficult to reasonably and efficiently schedule tasks in the cloud environment. Designing an excellent scheduling strategy plays an indispensable role in improving the operating performance of the cloud platform, shortening task response time, and improving user service satisfaction. [0003] The scale and quantity of tasks submitted by users to the cloud platform are very large, and there is no constraint relationship between the tasks submitted by multiple users. The tasks exist in parallel. How to reasona...

Claims

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Application Information

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IPC IPC(8): G06F9/50G06K9/62G06N3/12
CPCG06F9/505G06F9/5027G06F9/5077G06N3/126G06F2209/508G06F18/23
Inventor 周舟李方敏刘萍张韬杨志邦姚文静
Owner CHANGSHA UNIVERSITY
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