Resource allocation method based on budget constraints to minimize execution time of self-organized cloud tasks

A technology for task execution and resource allocation, which is applied in the field of computer networks, can solve problems such as not considering user task execution time and failing to meet user resource usage needs in a timely manner.

Active Publication Date: 2019-05-07
ZHEJIANG STARSINO INFORMATION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that this method does not consider the execution time of user tasks, so it cannot meet the user's demand for resources in time

Method used

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  • Resource allocation method based on budget constraints to minimize execution time of self-organized cloud tasks
  • Resource allocation method based on budget constraints to minimize execution time of self-organized cloud tasks
  • Resource allocation method based on budget constraints to minimize execution time of self-organized cloud tasks

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0049] The present invention is based on a budget-limited self-organizing cloud task execution time minimization resource allocation method, and the steps are as follows:

[0050] Step 1, self-organizing the working nodes in the cloud to collect the available resources of each physical node.

[0051] The working nodes in the ad hoc cloud collect the available resources of each physical node, wherein there are 2000 nodes in the ad hoc cloud, and the available resources of each physical node include CPU computing resources and disk read and write speed resources.

[0052] Step 2, self-organizing cloud worker nodes collect user task requests.

[0053] The working nodes in the self-organizing cloud collect the user's task requests. The task requests include the multi-dimensional resource vector required by each task and the budget cost per unit time for each task execution. The CPU computing resources required by the two tasks in the self-organizing cloud are [ 6, 8], unit, Gflop...

Embodiment 2

[0061] Step 1, self-organizing the working nodes in the cloud to collect the available resources of each physical node.

[0062] The working nodes in the self-organizing cloud collect the available resources of each physical node, wherein there are 12,000 nodes in the self-organizing cloud, and the available resources of each physical node include CPU computing resources, disk read and write speed resources and network bandwidth resources.

[0063] Step 2, self-organizing cloud worker nodes collect user task requests.

[0064] The working nodes in the self-organizing cloud collect the user's task requests. The task requests include the multi-dimensional task vector required by each task and the budget cost per unit time for each task execution. The CPU computing resources required by the two tasks in the self-organizing cloud are [ 5, 7], unit, Gflops, the disk read and write speed resources required by the two tasks in the self-organizing cloud are [3, 2], the unit, Gbps, and...

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PUM

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Abstract

The present invention provides a method for resource allocation based on budgetary constraints to minimize the execution time of self-organizing cloud tasks, comprising the following steps: Step 1, the working nodes in the self-organizing cloud collect the available resources of each physical node; Step 2, the working nodes in the self-organizing cloud Collect the user's task request; step 3, the working nodes in the self-organizing cloud use the differential evolution algorithm to allocate the virtual resources in the self-organizing cloud. The present invention provides a resource allocation method, which can fully tap CPU computing resources, disk read and write speed resources, and network bandwidth resources in self-organizing clouds, and dynamically allocate resources on demand from multiple dimensions with the goal of minimizing task execution time.

Description

technical field [0001] The invention belongs to the technical field of computer networks, in particular to a resource allocation method for minimizing the execution time of self-organized cloud tasks based on budget constraints. Background technique [0002] Cloud computing has become a compelling technology for deploying distributed services. The problem of resource allocation in cloud systems emphasizes how to utilize multi-attribute resources by reusing the operating system. With the development of virtual machine technology, cloud systems have been able to reuse some operating systems on the same hardware, and allow tasks to be executed on the underlying virtual machine without performance interference. The bottom layer of the virtual machine includes CPU, memory, storage, network bandwidth, etc. Since they can be dynamically configured for reasonable resource sharing, the cloud system can achieve fine-grained resource sharing. [0003] In recent years, various technol...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/917H04L29/08H04L47/76
Inventor 徐雷吕铜明王俊钱芳杨余旺
Owner ZHEJIANG STARSINO INFORMATION TECH
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