Method and system for self-adaptive on-demand resource allocation in a virtualized environment

A virtualized environment and resource allocation technology, applied in the field of resource allocation, self-adaptive on-demand resource allocation, can solve problems such as economic loss, waste of resources, impact on application performance, etc., to achieve good use of resources, reduce maintenance costs, and reduce startup time Effect

Active Publication Date: 2011-12-14
日照育成科技咨询服务有限责任公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Adjustment based on resource usage has the following disadvantages: (a) With the development of Internet applications, applications become more and more "big" and more complex, and the definition of expected resource usage becomes more and more appropriate. difficulty
If the definition is too high, it will affect the performance of the application
If the definition is too low, it will lead to waste of resources
(b) Accurate sampling of resource usage becomes more difficult in a virtualized environment due to the overhead of filtering the hypervisor
(c) When multiple virtual machines are running on the same physical machine, the accuracy of predicting the real resource demand based on the current measu

Method used

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  • Method and system for self-adaptive on-demand resource allocation in a virtualized environment
  • Method and system for self-adaptive on-demand resource allocation in a virtualized environment

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Experimental program
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Embodiment 2

[0082] 2) Embodiment 2: 1-PM:N-VM resource allocation strategy

[0083] Figure 6 It is a flow chart of the 1-PM:N-VM resource allocation strategy provided by Embodiment 2 of the present invention. In this embodiment, the method steps of the 1-PM:N-VM resource allocation strategy are:

[0084] Step 1: Use the request response time obtaining module 301 to obtain the actual response time of each request. Mark a connection according to , use the difference between request timestamp and response timestamp to get the actual response time of each request, and count each application i in the jth cycle Throughput T ij , set the expected response time as The statistical response time falls within the expected response time range The number of requests N ij and the response time falls into The number of requests on the left L ij or the response time falls into The number of requests on the right U ij . d ij is the measured response time of the i-th virtual machine in the ...

Embodiment 3

[0094] 3) Embodiment 3: virtual machine migration strategy

[0095] Figure 7 The flow chart of the virtual machine migration strategy provided by Embodiment 3 of the present invention, the method steps of the virtual machine migration strategy in this embodiment are:

[0096] Step 1: Use the physical machine resource monitoring module 401 to obtain the resource usage of each physical machine. Define an upper and lower limit for resource usage for each physical machine.

[0097] Step 2: Determine whether the resource usage is greater than the upper limit?

[0098] If it is greater than the upper limit, it is calculated according to the following formula:

[0099] W 1 *VM memory amount+W 2 *VM memory dirty page rate+W 3 / VM's CPU load (Equation 7)

[0100] The virtual machine with the smallest value is selected for migration. This is because according to experimental analysis, the overhead of virtual machine migration is mainly related to the amount of memory occupied b...

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Abstract

The invention discloses a system for adaptively allocating resources as required in a virtualization environment. The system comprises a dynamic perception request distribution module, a 1-physical machine (PM):N-virtual machine (VM) module and a data center global management module, wherein the 1-PM:N-VM module allocates the resources on a PM according to user experiences which are collected in real time; the dynamic perception request distribution module distributes loads to proper VMs according to monitored application request load information and VM volume information and responds to requests; and the data center global management module judges whether the VMs are required to migrate between the PMs to be re-placed according to collected PM resource load information, and judges whether a new PM is released or applied to an idle resource pool to quit or enter application service when the PM is excess or insufficient. The invention also discloses a method for adaptively allocating the resources as required in the virtualization environment. The method comprises an adaptive VM dynamic volume perception request distribution strategy, a 1-PM:N-VM resource allocation strategy and a VM migration strategy. The invention has an application prospect in the technical field of computers.

Description

(1) Technical field [0001] The invention relates to resource allocation, in particular to a method and system for self-adaptive on-demand resource allocation in a virtualized environment, and belongs to the technical field of computers. (2) Background technology [0002] With the rapid development of Internet applications, more and more service providers outsource their services to data centers, making the scale of data centers larger and more complex. Virtualization technology is playing an increasingly important role in building large-scale data centers due to its following characteristics: 1. Improve resource utilization of infrastructure. A physical machine (PM) can run multiple virtual machines (VM) at the same time, and the virtual machine monitor (VMM) provides more fine-grained resource allocation mechanism support, such as the default credit of xen (an open source virtualization product). Scheduling policy provides mechanism support for dynamic allocation of CPU re...

Claims

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Application Information

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IPC IPC(8): G06F9/50G06F9/48G06F9/455
Inventor 祝明发张伟徐威刘家军肖利民阮利
Owner 日照育成科技咨询服务有限责任公司
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