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Using time-series analysis to provide long-term CPU utilization prediction

Authors:

Daniel W. Yoas,

Greg SimcoAuthors Info & Claims

RIIT '14: Proceedings of the 3rd annual conference on Research in information technology

Pages 39 - 44

https://doi.org/10.1145/2656434.2656445

Published: 13 October 2014 Publication History

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Abstract

Time-series analysis has been a recognized method of prediction for years. In computing, prediction has revolved around scheduling problems and is used in computing time to manage resources in the short-term. Long-term prediction using these methods has proven to be problematic and of little use. However, with the rise of Information Technology (IT) and the need to manage resources in a business atmosphere, the need to provide long-term resource management remains a difficult problem without a good solution. At this time, IT professionals use experience and their best judgment to manage equipment and frequently purchase systems based on maximum requirements. The need to take the knowledge gained by computer science in scheduling now needs to be expanded into the realm of IT to facilitate a more economical use of resource availability. This work is just the first step and provides one path to accomplishing long-term prediction in computing.

References

[1]

Information Technology 2008: Curriculum Guidelines for Undergraduate Degree Programs in Information Technology. (2008). Retrived, from http://www.acm.org//education/curricula/IT2008%20Curriculum.pdf.

Google Scholar

[2]

Configuration Maximums: VMware vSphere 5.5. (2014). Retrived June 6, 2014, from http://www.vmware.com/pdf/vsphere5/r55/vsphere-55-configuration-maximums.pdf.

Google Scholar

[3]

Abusina, Z.U.M., S.M.S. Zabir, A. Ashir, D. Chakraborty, T. Suganuma, and N. Shiratori (2005) An engineering approach to dynamic prediction of network performance from application logs. Int. J. Netw. Manag. 15, 151--162

Digital Library

Google Scholar

[4]

Al-Ghamdi, M., A.P. Chester, and S.A. Jarvis (2010) Predictive and Dynamic Resource Allocation for Enterprise Applications. 10th IEEE International Conference on Computer and Information Technology (CIT 2010) 0, 2776--2783

Digital Library

Google Scholar

[5]

Andreolini, M. and S. Casolari (2006) Load prediction models in web-based systems. Proceedings of the 1st international conference on Performance evaluation methodolgies and tools, 27

Digital Library

Google Scholar

[6]

Andreolini, M., S. Casolari, and M. Colajanni (2008) Models and framework for supporting runtime decisions in Web-based systems. ACM Trans. Web 2, 1--43

Digital Library

Google Scholar

[7]

Davis, I.J., H. Hemmati, R.C. Holt, M.W. Godfrey, D.M. Neuse, and S. Mankovskii, Regression-based utilization prediction algorithms: an empirical investigation, in Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research. 2013, IBM Corp.: Ontario, Canada. p. 106--120.

Digital Library

Google Scholar

[8]

Dinda, P.A. (2002) A Prediction-Based Real-Time Scheduling Advisor. International Parallel and Distributed Processing Symposium (IPDPS'02) 1, 0010b-0010b

Crossref

Google Scholar

[9]

Istin, M., A. Visan, F. Pop, and V. Cristea (2010) Decomposition Based Algorithm for State Prediction in Large Scale Distributed Systems. Ninth International Symposium on Parallel and Distributed Computing 0, 17--24

Digital Library

Google Scholar

[10]

Krithikaivasan, B., Y. Zeng, K. Deka, and D. Medhi (2007) ARCH-based traffic forecasting and dynamic bandwidth provisioning for periodically measured nonstationary traffic. IEEE/ACM Trans. Netw. 15, 683--696

Digital Library

Google Scholar

[11]

Rood, B. and M.J. Lewis (2010) Availability Prediction Based Replication Strategies for Grid Environments. 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing 0, 25--33

Digital Library

Google Scholar

[12]

Wolski, R., N.T. Spring, and J. Hayes (1999) The network weather service: a distributed resource performance forecasting service for metacomputing. Future Gener. Comput. Syst. 15, 757--768

Crossref

Google Scholar

[13]

Yoas, D.W. and G. Simco, Resource utilization prediction: a proposal for information technology research, in Proceedings of the 1st Annual conference on Research in information technology. 2012, ACM: Calgary, Alberta, Canada. p. 25--30.

Digital Library

Google Scholar

[14]

Zhao, W. and Z. Wang, Dynamic memory balancing for virtual machines, in Proceedings of the 2009 ACM SIGPLAN/SIGOPS international conference on Virtual execution environments. 2009, ACM: Washington, DC, USA. p. 21--30.

Digital Library

Google Scholar

Cited By

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Jha SSangwan VBalani SNagrath PSaini D(2024)Optimizing CPU Resources: A Deep Learning Approach for Usage Forecasting in Cloud EnvironmentsProceedings of the 5th International Conference on Information Management & Machine Intelligence10.1145/3647444.3647869(1-8)Online publication date: 13-May-2024
https://doi.org/10.1145/3647444.3647869

Index Terms

Using time-series analysis to provide long-term CPU utilization prediction
1. General and reference
  1. Cross-computing tools and techniques
    1. Measurement
    2. Performance
2. Software and its engineering
  1. Software creation and management
    1. Software development process management
      1. Software development methods
  2. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Process management
        Monitors

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RIIT '14: Proceedings of the 3rd annual conference on Research in information technology

October 2014

98 pages

ISBN:9781450327114

DOI:10.1145/2656434

General Chairs:
Becky Rutherfoord
Southern Polytechnic State University, USA
,
Lei Li
Southern Polytechnic State University, USA
,
Susan Van de Ven
Southern Polytechnic State University, USA
,
Program Chairs:
Amber Settle
DePaul University, USA
,
Terry Steinbach
DePaul University, USA

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New York, NY, United States

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Published: 13 October 2014

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SIGITE/RIIT'14: SIGITE/RIIT 2014

October 15 - 18, 2014

Georgia, Atlanta, USA

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Jha SSangwan VBalani SNagrath PSaini D(2024)Optimizing CPU Resources: A Deep Learning Approach for Usage Forecasting in Cloud EnvironmentsProceedings of the 5th International Conference on Information Management & Machine Intelligence10.1145/3647444.3647869(1-8)Online publication date: 13-May-2024
https://doi.org/10.1145/3647444.3647869

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CPU utilization prediction methods overview

Resource utilization prediction: long term network web service traffic

Resource utilization prediction: a proposal for information technology research

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