Skip to main content
SpringerLink
Log in

Software Monitoring in Data Centers

  • Chapter
  • First Online:
Handbook on Data Centers

Abstract

In recent years, thousands of commodity servers have been deployed in Internet data centers to run large scale Internet applications or cloud computing services. How to continuously monitor the availability, performance and security of data centers in real-time operational environments becomes a daunting task. In this chapter, a comprehensive solution for software monitoring is discussed in Internet data centers.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Boulon J, Konwinski A, Qi R, et al. Chukwa: a large-scale monitoring system//Proceedings of IEEE International Conference on Control Applications, 2008, 8.

    Google Scholar 

  2. http://blog.sina.com.cn/s/blog_5433a9f80100byg0.html

  3. http://en.wikipedia.org/wiki/Software_aging

  4. Cheng S, Pan Y, Analysis of cloud service reliability model based on node failure recovery. Journal of Software Guide, 2012, 11 (5): 90–92.

    Google Scholar 

  5. Sahoo R K, Squillante M S, Sivasubramaniam A, et al., Failure data analysis of a large-scale heterogeneous server environment//IEEE International Conference on Dependable Systems and Networks, 2004: 772–781.

    Google Scholar 

  6. Heath T, Martin R P, Nguyen T D, Improving cluster availability using workstation validation. ACM SIGMETRICS Performance Evaluation Review, 2002, 30(1): 217–227.

    Article  Google Scholar 

  7. http://www.d1net.com/cloud/xaas/88623.html

  8. Shang Y, Li D, Xu M, Energy-aware routing in data center network//Proceedings of the first ACM SIGCOMM Workshop on Green Networking, 2010: 1–8.

    Google Scholar 

  9. Srikantaiah S, Kansal A, Zhao F., Energy aware consolidation for cloud computing//Proceedings of the Conference on Power Aware Computing and Systems. USENIX Association, 2008, 10.

    Google Scholar 

  10. HOOPER A. Green computing. Communications of the ACM, 2008, 51(10): 1–13.

    Google Scholar 

  11. Avizienis A, Laprie J C, Randell B, et al., Basic concepts and taxonomy of dependable and secure computing. IEEE Transactions on Dependable and Secure Computing, 2004, 1(1): 11–33.

    Article  Google Scholar 

  12. Dawson D, Desmarais R, Kienle H M, et al., Monitoring in adaptive systems using reflection//Proceedings of the International Workshop on Software Engineering for Adaptive and Self-managing Systems, 2008: 81–88.

    Google Scholar 

  13. http://baike.baidu.com/view/23710.html.

  14. Zhang Y, Li, Zhang J, et al., Reviewed on middleware technology. Computer Engineering and Applications, 2002, 15(1): 80–82.

    Google Scholar 

  15. Lin Z, Lai Y, Lin C, et al., The research on cloud database. Journal of Software, 2012, 23(5):1148–1166.

    Article  MATH  MathSciNet  Google Scholar 

  16. Chang F, Dean J, Ghemawat S, et al., Bigtable: A distributed storage system for structured data. ACM Transactions on Computer Systems (TOCS), 2008, 26(2): 4–11.

    Article  Google Scholar 

  17. Web Services Architecture [S],W3C Working Draft, 2002. http://www.w3.org/TR/ws-arch.

  18. Bai X, Liu Y, Wang L, et al., Model-based monitoring and policy enforcement of services. Simulation Modelling Practice and Theory, 2009, 17(8): 1399–1412.

    Article  Google Scholar 

  19. Delgado N, Gates A Q, Roach S. A taxonomy and catalog of runtime software-fault monitoring tools. IEEE Transactions on Software Engineering, 2004, 30(12): 859–872.

    Article  Google Scholar 

  20. Da Cruz S M S, Campos M L M, Pires P F, et al., Monitoring e-business Web services usage through a log based architecture//Proceeding of IEEE International Conference on Web Services, 2004: 61–69.

    Google Scholar 

  21. Sahai A, Graupner S, Machiraju V, et al. Specifying and monitoring guarantees in commercial grids through SLA//Proceedings of 3rd IEEE International Symposium on Cluster Computing and the Grid, 2003: 292–299.

    Google Scholar 

  22. Devine S W, Bugnion E, Rosenblum M. Virtualization system including a virtual machine monitor for a computer with a segmented architecture: U.S. Patent 6,397, 242, 2002-5-28.

    Google Scholar 

  23. http://www.connectix.com/products/vs.html.

  24. Barham P, Dragovic B, Fraser K, et al., Xen and the art of virtualization. ACM SIGOPS Operating Systems Review, 2003, 37(5): 164–177.

    Article  Google Scholar 

  25. Kivity A, Kamay Y, Laor D, et al., KVM: the Linux virtual machine monitor//Proceedings of the Linux Symposium, 2007(1): 225–230.

    Google Scholar 

  26. Agichtein E, Brill E, Dumais S., Improving web search ranking by incorporating user behavior information//Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2006: 19–26.

    Google Scholar 

  27. Shin J, Narayanan S S, Gerber L, et al. Analysis of user behavior under error conditions in spoken dialogs//INTERSPEECH. 2002.

    Google Scholar 

  28. Granka L A, Joachims T, Gay G., Eye-tracking analysis of user behavior in WWW search//Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. 2004: 478–479.

    Google Scholar 

  29. Bellare M, Miner S K. A forward-secure digital signature scheme//Advances in Cryptology—CRYPTO’99. Springer Berlin Heidelberg, 1999: 431–448.

    Google Scholar 

  30. Günther C G. An identity-based key-exchange protocol//Advances in Cryptology—Eurocryp ’89. Springer Berlin Heidelberg, 1990: 29–37.

    Google Scholar 

  31. Padala P, Hou K Y, Shin K G, et al. Automated control of multiple virtualized resources//Proceedings of the 4th ACM European Conference on Computer Systems, 2009: 13–26.

    Google Scholar 

  32. Lowe S. Mastering VMware vSphere 4. Indianapolis: Wiley Publishing, 2009.

    Google Scholar 

  33. Matthews J N, Dow E M, Deshane T, et al., Running Xen: a hands-on guide to the art of virtualization. Prentice Hall PTR, 2008.

    Google Scholar 

  34. Williams D E. Virtualization with Xen (tm): Including XenEnterprise, XenServer, and XenExpress: Including XenEnterprise, XenServer, and XenExpress.Syngress, 2007.

    Google Scholar 

  35. SzymańskaKwiecień A, Kwiatkowski J, Pawlik M, et al., Performance prediction methods//Proceedings of the International Multiconference. 2006, 1896: 7094.

    Google Scholar 

  36. Kwiatkowski J. Evaluation of parallel programs by measurement of its granularity//Parallel Processing and Applied Mathematics. Springer Berlin Heidelberg, 2006: 145–153.

    Google Scholar 

  37. Jin’an Hu. The data centers in the cloud computing resources monitoring system research and design. Journal of University of Electronic Science and Technology. 2012.5.

    Google Scholar 

  38. ZHAO Fang, LI Lan-ying. Study of web application monitoring system based on business process. Journal of Beijing Forestry University. 2013.6.

    Google Scholar 

  39. Wikipedia, the resource monitor[OL]. http://en.wikipedia.org/wiki/Resource_Monitor.

  40. Han F, Peng J, Zhang W, et al. Virtual resource monitoring in cloud computing. Journal of Shanghai University (English Edition), 2011, 15: 381–385.

    Article  Google Scholar 

  41. Fastest VPN for Asia. How to use the resource monitor in vista. http://www.vistax64.com/tutorials/111020-resource-monitor.html

  42. Manage Engine-IT Enterprise Management. CPU, Memory and Disk Monitoring [OL]. http://www.manageengine.com/network-monitoring/cpu-memory-disk.html

  43. Zhuohao Wang, Zhuofeng Zhao. A Model-Driven Approach for Business-Oriented Monitoring of Service Operation//Proceeding of IEEE International Conference on Service Sciences (ICSS). 2010, 5:13–14.

    Google Scholar 

  44. Thomas M, Redmond R, Yoon V, et al. A semantic approach to monitor business process. Communications of the ACM, 2005, 48(12): 55–59.

    Article  Google Scholar 

  45. Ince D C, Andrews D. The Software Life Cycle. Butterworth-Heinemann, 1990.

    Google Scholar 

  46. Kleinrock L. A vision for the Internet. ST Journal of Research, 2005, 2(1): 4–5.

    Google Scholar 

  47. Buyya R, Beloglazov A, Abawajy J., Energy-efficient man-agement of data center resources for cloud computing:a vision, architectural elements, and open challenges//Proceeding of the 2010 International Conference on Parallel and Distributed Processing Techniques and Applications,2010:1–12.

    Google Scholar 

  48. Weiss A. Computing in the clouds. Networker, 2007, 11(4):16–25.

    Article  Google Scholar 

  49. Barham P, Dragovic B, Fraser K, et al. Xen and the art of virtualization. ACM SIGOPS Operating Systems Review, 2003, 37(5): 164–177.

    Article  Google Scholar 

  50. Padala P, Shin K G, Zhu X, et al. Adaptive control of virtualized resources in utility computing environments. ACM SIGOPS Operating Systems Review, 2007, 41(3): 289–302.

    Article  Google Scholar 

  51. Marston S, Li Z, Bandyopadhyay S, et al. Cloud Computing—The business perspective. Decision Support Systems, 2011, 51(1): 176–189.

    Article  Google Scholar 

  52. Xiong K, Perros H. Service performance and analysis in cloud computing//Proceeding of IEEE 2009 World Conference on Services-I, 2009: 693–700.

    Google Scholar 

  53. http://www.brighthub.com/computing/smb-security/articles/11337.aspx.

  54. http://www.wisegeek.com/what-is-software-development.htm.

  55. http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=39064

  56. Eick S G, Graves T L, Karr A F, et al. Does code decay? assessing the evidence from change management data. IEEE Transactions on Software Engineering, 2001, 27(1): 1–12.

    Article  Google Scholar 

  57. FormalOn-SiteMonitoringApril7, 2006. http://www.research.ucsf.edu/chr/Forms/chrOnsiteMonit.asp

  58. Contact Hole Roughness (CHR). http://www.research.ucsf.edu/chr/Forms/chrOnsiteMonit.asp

  59. Vaculín R, Sycara K. Semantic web services monitoring: An OWL-S based approach//Proceedings of the 41st Annualon IEEE Hawaii International Conference on System Sciences, 2008: 313–313.

    Google Scholar 

  60. Dan A, Davis D, Kearney R, et al. Web services on demand: WSLA-driven automated management. IBM Systems Journal, 2004, 43(1): 136–158.

    Article  Google Scholar 

  61. Lundy L, Pradeep R. On the migration from enterprise management to integrated service level management. IEEE on Network, 2002, 16(1): 8–14.

    Article  Google Scholar 

  62. Avery, Robert B., Off-Site Surveillance Systems. History of the Eighties: Lessons for the Futur,1997,2:25–29.

    Google Scholar 

  63. Snodgrass R. A relational approach to monitoring complex systems. ACM Transactions on Computer Systems (TOCS), 1988, 6(2): 157–195.

    Article  Google Scholar 

  64. De Chaves S A Uriarte R B Westphall C B. Toward an Architecture for Monitoring Private Clouds. IEEE on Communication Magazine, 2011, 49(12): 130–137.

    Article  Google Scholar 

  65. Saaty T L. What is the analytic hierarchy process? [M]. Springer Berlin Heidelberg, 1988.

    Google Scholar 

  66. Sun Z, Xu Z, Da Q. A Model Based on Alternative Similarity Scale for Uncertain Multi-Attribute Decision-Making. Journal of Management Science, 2001, 9(6): 58–62.

    Google Scholar 

  67. Wu D, Cheng H, Xi X, et al. Annual Peak Power Load Forecasting Based on Fuzzy AHP//Proceedings of the Chinese Society of Universities for Electric Power System and Automation, 2007, 1: 009.

    Google Scholar 

  68. Keufmann A, Gupta M M. Introduction to Fuzzy Arithmetic:Theory and Application. NY: Van Nostrand Reinhold, 1991.

    Google Scholar 

  69. Liu H, Kong F. A new MADM algorithm based on fuzzy subjective and objective integrated weights. International Journal of Information System and Sciences, 2005, 1(3–4): 420–427.

    MATH  Google Scholar 

  70. Kukavica I, Robinson J C. Distinguishing smooth functions by a finite number of point values, and a version of the Takens Embedding Theorem. Physica D: Nonlinear Phenomena, 2004, 196(1): 45–66.

    Article  MATH  MathSciNet  Google Scholar 

  71. Kember G, Fowler A C. A Correlation Function for Choosing Time Delays in Phase Portrait Reconstructions. Physics Letters A, 1993, 179(2): 72–80.

    Article  MathSciNet  Google Scholar 

  72. Rosenstein M T, Collins J J, De Luca C J. A Practical Method for Calculating Largest Lyapunov Exponents From Small Data Sets. Physica D: Nonlinear Phenomena, 1993, 65(1): 117–134.

    Article  MATH  MathSciNet  Google Scholar 

  73. Chambers J M. Graphical Methods for Data Analysis.Spring Science, 1983.

    Google Scholar 

  74. Gao J, Pattabhiraman P, Bai X, et al. SaaS Performance and Scalability Evaluation in Clouds//Proceeding of IEEE the 6th International Symposium on Service Oriented System Engineering (SOSE), 2011: 61–71.

    Google Scholar 

  75. Guo J, Huang H, Wang B, et al. Research on the prediction of web application system aging trend oriented to user access intention.Instrumentation, Measurement, Circuits and Systems. Springer Berlin Heidelberg, 2012: 983–991.

    Google Scholar 

  76. HP LoadRunner—Free download and Software Reviews—CNET Download.com. http://download.cnet.com/HP-LoadRunner/3000-2383_4-10306263.html#ixzz2a39AvT61.

  77. Load Runner Load Testing Tools Resources. http://www.load-testing-tools.com/loadrunner.html.

  78. Brown A, Johnston S K, Larsen G, et al. SOA Development Using the IBM Rational Software Development Platform: APractical Guide.Rational Software, 2005.

    Google Scholar 

  79. Apache JMeter, ApacheCon North America Portland, Oregon 26th–28th February 2013, http://jmeter.apache.org

Download references

Author information

Authors and Affiliations

  1. Northeastern University, Shenyang, People’s Republic China

    Chengdong Wu & Jun Guo

Authors
  1. Chengdong Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jun Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chengdong Wu .

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, North Dakota State University, Fargo, North Dakota, USA

    Samee U. Khan

  2. School of Information Technologies, The University of Sydney, Sydney, New South Wales, Australia

    Albert Y. Zomaya

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this chapter

Cite this chapter

Wu, C., Guo, J. (2015). Software Monitoring in Data Centers. In: Khan, S., Zomaya, A. (eds) Handbook on Data Centers. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2092-1_42

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2092-1_42

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4939-2091-4

  • Online ISBN: 978-1-4939-2092-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation