A prefetching framework for the streaming loading of virtual software

Liang Zhong; Junbin Kang; Chunming Hu; Tianyu Wo; Haibing Zheng; Bo Li

doi:10.1109/ICPADS.2010.25

A prefetching framework for the streaming loading of virtual software

Liang Zhong^*
, Junbin Kang
, Chunming Hu
, Tianyu Wo
, Haibing Zheng
, Bo Li

^*Corresponding author for this work

School of Software

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In recent years, the Software as a Service, largely enabled by the Internet, has become an innovative software delivery model. During the streaming execution of virtualization software, the execution will wait until the missing data was downloaded, which greatly influences the user experience. In this paper, we present a block-level prefetching framework for streaming delivery of software based on N-Gram prediction model and an incremental data mining algorithm. The prefetching framework uses the historical block access logs for data mining, then dynamically updates and polishes the prefetching rules. The experimental results show that this prefetching framework achieves a launch time reduced by 10% to 50%, as well as hit rate between 81% and 97%.

Original language	English
Title of host publication	Proceedings - 16th International Conference on Parallel and Distributed Systems, ICPADS 2010
Pages	712-717
Number of pages	6
DOIs	https://doi.org/10.1109/ICPADS.2010.25
State	Published - 2010
Event	16th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2010 - Shanghai, China Duration: 8 Dec 2010 → 10 Dec 2010

Publication series

Name	Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS
ISSN (Print)	1521-9097

Conference

Conference	16th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2010
Country/Territory	China
City	Shanghai
Period	8/12/10 → 10/12/10

Keywords

Log mining
Prefetching
Saas
Streaming deliverying

Access to Document

10.1109/ICPADS.2010.25

Cite this

Zhong, L., Kang, J., Hu, C., Wo, T., Zheng, H., & Li, B. (2010). A prefetching framework for the streaming loading of virtual software. In Proceedings - 16th International Conference on Parallel and Distributed Systems, ICPADS 2010 (pp. 712-717). Article 5695671 (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS). https://doi.org/10.1109/ICPADS.2010.25

@inproceedings{0522c2349faa475989f30f6d8e044c68,

title = "A prefetching framework for the streaming loading of virtual software",

abstract = "In recent years, the Software as a Service, largely enabled by the Internet, has become an innovative software delivery model. During the streaming execution of virtualization software, the execution will wait until the missing data was downloaded, which greatly influences the user experience. In this paper, we present a block-level prefetching framework for streaming delivery of software based on N-Gram prediction model and an incremental data mining algorithm. The prefetching framework uses the historical block access logs for data mining, then dynamically updates and polishes the prefetching rules. The experimental results show that this prefetching framework achieves a launch time reduced by 10\% to 50\%, as well as hit rate between 81\% and 97\%.",

keywords = "Log mining, Prefetching, Saas, Streaming deliverying",

author = "Liang Zhong and Junbin Kang and Chunming Hu and Tianyu Wo and Haibing Zheng and Bo Li",

year = "2010",

doi = "10.1109/ICPADS.2010.25",

language = "英语",

isbn = "9780769543079",

series = "Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS",

pages = "712--717",

booktitle = "Proceedings - 16th International Conference on Parallel and Distributed Systems, ICPADS 2010",

note = "16th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2010 ; Conference date: 08-12-2010 Through 10-12-2010",

}

Zhong, L, Kang, J, Hu, C , Wo, T, Zheng, H & Li, B 2010, A prefetching framework for the streaming loading of virtual software. in Proceedings - 16th International Conference on Parallel and Distributed Systems, ICPADS 2010., 5695671, Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS, pp. 712-717, 16th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2010, Shanghai, China, 8/12/10. https://doi.org/10.1109/ICPADS.2010.25

A prefetching framework for the streaming loading of virtual software. / Zhong, Liang; Kang, Junbin; Hu, Chunming et al.
Proceedings - 16th International Conference on Parallel and Distributed Systems, ICPADS 2010. 2010. p. 712-717 5695671 (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A prefetching framework for the streaming loading of virtual software

AU - Zhong, Liang

AU - Kang, Junbin

AU - Hu, Chunming

AU - Wo, Tianyu

AU - Zheng, Haibing

AU - Li, Bo

PY - 2010

Y1 - 2010

N2 - In recent years, the Software as a Service, largely enabled by the Internet, has become an innovative software delivery model. During the streaming execution of virtualization software, the execution will wait until the missing data was downloaded, which greatly influences the user experience. In this paper, we present a block-level prefetching framework for streaming delivery of software based on N-Gram prediction model and an incremental data mining algorithm. The prefetching framework uses the historical block access logs for data mining, then dynamically updates and polishes the prefetching rules. The experimental results show that this prefetching framework achieves a launch time reduced by 10% to 50%, as well as hit rate between 81% and 97%.

AB - In recent years, the Software as a Service, largely enabled by the Internet, has become an innovative software delivery model. During the streaming execution of virtualization software, the execution will wait until the missing data was downloaded, which greatly influences the user experience. In this paper, we present a block-level prefetching framework for streaming delivery of software based on N-Gram prediction model and an incremental data mining algorithm. The prefetching framework uses the historical block access logs for data mining, then dynamically updates and polishes the prefetching rules. The experimental results show that this prefetching framework achieves a launch time reduced by 10% to 50%, as well as hit rate between 81% and 97%.

KW - Log mining

KW - Prefetching

KW - Saas

KW - Streaming deliverying

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DO - 10.1109/ICPADS.2010.25

M3 - 会议稿件

AN - SCOPUS:79951745953

SN - 9780769543079

T3 - Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS

SP - 712

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BT - Proceedings - 16th International Conference on Parallel and Distributed Systems, ICPADS 2010

T2 - 16th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2010

Y2 - 8 December 2010 through 10 December 2010

ER -

A prefetching framework for the streaming loading of virtual software

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Keywords

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