Automatic software deployment using user level virtualization for cloud computing
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Automatic software deployment using user-level virtualization for cloud-computing. Future Generation Computer System (2013) Youhui Zhang, Yanhua Li, Weimin Zheng. Outline. Introduction The framework Performance test Conclusion. Introduction (1).

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Automatic software deployment using user level virtualization for cloud computing

Automatic software deployment using user-level virtualization for cloud-computing

Future Generation Computer System (2013)

Youhui Zhang, Yanhua Li, Weimin Zheng


Outline
Outline

  • Introduction

  • The framework

  • Performance test

  • Conclusion


Introduction 1
Introduction (1)

  • Infrastructure cloud service providers deliver virtual hardware and system software in their datacenters, based on the demand from customers

  • It is necessary to deploy application software in similar way


Virtual appliances vas
Virtual Appliances (VAs)

  • It is a pre-built software

  • VA-based method can reduce time and expenses


Va drawbacks
VA drawbacks

  • Lack of flexibility

  • Inefficiency of storage


Lack of flexibility
Lack of flexibility

  • Customer needs software Aand B to work together in a virtual machine, but the provideronly has two separate VAs containing A and B respectively

  • The provider has to create a new VM template to combine A and Btogether


Inefficiency of storage
Inefficiency of storage

  • OS has to be combined. Therefore, the storage overhead


Introduction 2
Introduction (2)

  • This paper introduces mechanisms to isolate application software from OS

  • Application software can be deployed in a fine granularity to increase the flexibility and decrease the storage overhead

  • We call such application software as on-demand software


Function1 software preparation
Function1 - Software preparation

  • Cover software into the on-demand mode

  • On-demand software is stored in the software depository for users’ selection


Preparation of on demand software
Preparation of on-demand software

  • software can be regarded as containing three parts:

    • Part1 includes all resources provided by the OS

    • Part2 contains what are created/ modified/ deleted by the installation process

    • Part3 is the data created/modified/deleted during the run time


Preparation of on demand software cont d
Preparation of on-demand software(cont’ d)


Preparation of on demand software cont d1
Preparation of on-demand software(cont’ d)

  • Snapshot is taken to build the on-demand software


Function2 software selection
Function2 - Software selection

  • A customer can choose the wanted OS, as well as any number of software in separated stages


Function3 on demand deployment
Function3 - On-demand deployment

  • When the customer actually uses the chosen software, will it be streamed from the data server and run locally without installation.


The runtime environment of on demand software cont d
The runtime environment of on-demand software (cont’ d)

  • The resource modified will be moved into Part 3


The runtime environment of on demand software
The runtime environment of on-demand software

  • Construct a runtime environment where software can locate and access any necessary resources

  • Runtime environment redirects all accesses for Parts 2 and 3 to the actual storage positions and guides other visits (for Part 1) to the local OS


User level file system
User-level file system

  • On-demand software is stored in the central depository and presented as files/ folders on a virtual local drive in the customer’s VM


Function4 software customization
Function4 - Software customization

  • The VA-based solution, it is difficult to implement this function efficiently


On demand software vs virtual appliance va
On-demand software VS Virtual appliance(VA)



Optimizations
Optimizations

  • Content-addressable storage

  • Data cache


Content addressable storage
Content-addressable storage

  • On-demandsoftware is partitioned into shards

  • Compute the hash valueof every shard, and the same values mean the corresponding shardsare identical.


Data cache
Data cache

  • The replace strategy is based on the usagefrequency




Conclusion
Conclusion

  • This paper provides a framework to decouple application software from VM images to improve the deployment flexibility for cloud computing

  • Compared with VA-based solutions, it also improves the storage efficiency

  • Users’ customization can been separated inherently and efficiently for reuse


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