Skip to main content
Springer Nature Link
Log in

Adaptive Web QoS controller based on online system identification using quantum-behaved particle swarm optimization

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Web quality of service (QoS) control can effectively prevent a Web Server from becoming overloaded. This paper presents an adaptive controller for Web QoS, which dynamically adjusts parameters of the proportional-integral (PI) controller according to the changes of the Web server model. Different from the existing methods based on the off-line system identification, the adaptive Web QoS controller is implemented based on the online system identification through a quantum-behaved particle swarm optimization (QPSO) algorithm and a mutated version of QPSO (MuQPSO). The proposed approach for online system identification by QPSO and MuQPSO shows better performance than genetic algorithms and the particle swarm optimization algorithm on the simulation tests. Then, the performance of the adaptive controller for Web QoS is tested in three experiments and compared with that of fixed PI controller. Experimental results show that the adaptive control employing online system identification by QPSO and MuQPSO algorithms is able to control the Web server resource more effectively in case of overload and, thus, improves the Web QoS.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Apache web server. http://www.apache.org/

  • Abdelzaher TF, Shin KG, Bhatti N (2002) Performance guarantees for web server end-systems: a control-theoretical approach. IEEE Trans Parallel Distrib Syst 13(1):80–96

    Article  Google Scholar 

  • Angeline PJ (1998) Evolutionary optimization versus particle swarm optimization: philosophy and performance differences. Evol Program VII Lect Notes Comput Sci 1447:601–610

    Article  Google Scholar 

  • Chen X, Chen H, Mohapatra P (2003) Aces: an efficient admission control scheme for qos-aware web servers. Comput Commun 26(14):1581–1593

  • Cheng S-T, Chen C-M, Chen I-R (2003) Performance evaluation of an admission control algorithm: dynamic threshold with negotiation. Perform Eval 52(1):1–13

    Article  Google Scholar 

  • Cherkasova L, Phaal P (2002) Session-based admission control: a mechanism for peak load management of commercial web sites. IEEE Trans Comput 51(6):669–685

    Article  Google Scholar 

  • Clerc M (1999) The swarm and the queen: towards a deterministic and adaptive particle swarm optimization. In: Proceedings of the 1999 congress on evolutionary computation, vol 3, pp 1951–1957

  • Clerc M, Kennedy J (2002) The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans Evol Comput 6(1):58–73

    Article  Google Scholar 

  • Diao Y, Gandhi N, Hellerstein JL, Parekh S, Tilbury DM (2002) Using mimo feedback control to enforce policies for interrelated metrics with application to the apache web server. In: IEEE/IFIP network operations and management symposium, pp 219–234

  • Fang W, Sun J, Ding Y (2010a) A review of quantum-behaved particle swarm optimization. IETE Tech Rev 27(4):336

    Article  Google Scholar 

  • Fang W, Sun J, Xu W (2010b) A new mutated quantum-behaved particle swarm optimizer for digital iir filter design. EURASIP J Adv Signal Process 2009(1):367465

  • Gilly K, Juiz C, Thomas N, Puigjaner R (2012) Adaptive admission control algorithm in a qos-aware web system. Inf Sci 199:58–77

    Article  Google Scholar 

  • Guitart J, Carrera D, Beltran V, Torres J,Ayguade E (2005) Session-based adaptive overload control for secure dynamic web applications. In: IEEE, international conference on parallel processing, pp 341–349

  • Jiang Y, Meng D (2007) Enforcing admission control using admission-time-ratio and pi controller. Jisuanji Yanjiu yu Fazhan (Computer Research and Development) 44(1):65–70

    MathSciNet  Google Scholar 

  • Kennedy J (2003) Bare bones particle swarms. In: Proceedings of the 2003 IEEE swarm intelligence symposium, pp 80–87

  • Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, pp 1942–1948

  • Kihl M, Robertsson A, Andersson M, Wittenmark B (2008) Control-theoretic analysis of admission control mechanisms for web server systems. World Wide Web 11(1):93–116

    Article  Google Scholar 

  • Li Y, Xiang R, Jiao L, Liu R (2012) An improved cooperative quantum-behaved particle swarm optimization. Soft Comput 16(6):1061–1069

  • Loudini M, Rezig S, Salhi Y (2013) Incorporate intelligence into the differentiated services strategies of a web server: an advanced feedback control approach. J Internet Serv Appl 4(1):1–16

    Article  Google Scholar 

  • Lu C, Abdelzaber TF, Stankovic JA, Son SH (2001) A feedback control approach for guaranteeing relative delays in web servers. In: Seventh IEEE real-time technology and applications symposium, pp 51–62

  • Lu Y, Abdelzaher TK, Saxena A (2004) Design, implementation, and evaluation of differentiated caching services. IEEE Trans Parallel Distrib Syst 15(5):440–452

    Article  Google Scholar 

  • Lu C, Lu Y, Abdelzaher TF, Stankovic JA, Son SH (2006) Feedback control architecture and design methodology for service delay guarantees in web servers. IEEE Trans Parallel Distrib Syst 17(9):1014–1027

    Article  Google Scholar 

  • Lu J, Dai G, Mu D, Yu J, Li H (2011) Qos guarantee in tomcat web server: a feedback control approach. In: IEEE, 2011 international conference on cyber-enabled distributed computing and knowledge discovery (CyberC), pp 183–189. ISBN: 1457718278

  • Mosberger D, Jin T (1998) Httperfa tool for measuring web server performance. ACM SIGMETRICS Perform Eval Rev 26(3):31–37

    Article  Google Scholar 

  • Muppala S, Zhou X (2011) Coordinated session-based admission control with statistical learning for multi-tier internet applications. J Netw Comput Appl 34(1):20–29

    Article  Google Scholar 

  • Netcraft (2013) web server survey, 2013

  • Palade V, Puscasu G, Neagu D (1999) Neural network-based control by inverting neural models. Control Eng Appl Inf 1:25–35

    Google Scholar 

  • Pateriya RK (2012) Web server load management with adaptive ssl and admission control mechanism. In: 2012 7th international conference on computer science and education (ICCSE), pp 1178–1183

  • Shi Y, Eberhart RC (1998) A modified particle swarm optimizer. In: Proceedings of the IEEE international conference on evolutionary computation. Piscataway, IEEE Press, pp 69–73

  • Shi Y, Eberhart RC (1999) Empirical study of particle swarm optimization. In: Proceedings of the 1999 congress on evolutionary computation, vol 3, pp 1945–1950

  • Sun J, Fang W, Palade V (2011) Quantum-behaved particle swarm optimization with gaussian distributed local attractor point. Appl Math Comput 218(7):3763–3775

    Article  MATH  Google Scholar 

  • Sun J, Fang W, Palade V (2012a) Quantum-behaved particle swarm optimization: analysis of individual particle behavior and parameter selection. Evol Comput 20(3):349–393

    Article  Google Scholar 

  • Sun J, Wu X, Fang W, Ding Y, Long H, Xu W (2012b) Multiple sequence alignment using the hidden markov model trained by an improved quantum-behaved particle swarm optimization. Inf Sci 182(1):93–114

    Article  MATH  MathSciNet  Google Scholar 

  • Sun J, Wu X, Palade V, Fang W, Lai C-H, Xu W (2012c) Convergence analysis and improvements of quantum-behaved particle swarm optimization. Inf Sci 193:81–103

    Article  MathSciNet  Google Scholar 

  • Sun J, Feng B, Xu W (2004a) Particle swarm optimization with particles having quantum behavior. In: IEEE congress on evolutionary computation, pp 325–331

  • Sun J, Xu W, Feng B (2004b) A global search strategy of quantum-behaved particle swarm optimization. IEEE Conf Cybernet Intell Syst 1:111–116

    Google Scholar 

  • Voigt T, Per G (2002) Adaptive resource-based web server admission control. In: Seventh international symposium on computers and communications, pp 219–224

  • Zhang Y, Gong D-W, Sun X-Y, Na G (2013) Adaptive bare-bones particle swarm optimization algorithm and its convergence analysis. Soft Comput 18(7):1337–1352

  • ZonaResearch (2001) The need for speed ii. Zona Market Bull 5:1–9

    Google Scholar 

Download references

Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant Nos. 61105128, 61170119, 61373055), by the Natural Science Foundation of Jiangsu Province, China (Grant Nos. BK20131106, BK20130161), by the Fundamental Research Funds for the Central Universities (Grant No. JUSRP51410B), by the Program for New Century Excellent Talents in University (Grant No. NCET-11-0660), by the RS-NSFC International Exchange Program (Grant No. 61311130141), by the 111 Project (Grant No. B12018), by PAPD of Jiangsu Higher Education Institutions.

Author information

Authors and Affiliations

  1. Key Laboratory of Advanced Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi ,  214122, China

    Wei Fang, Jun Sun & Xiaojun Wu

  2. Department of Computing, Coventry University, Coventry, UK

    Vasile Palade

Authors
  1. Wei Fang
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Jun Sun
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Xiaojun Wu
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Vasile Palade
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Wei Fang.

Additional information

Communicated by V. Loia.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fang, W., Sun, J., Wu, X. et al. Adaptive Web QoS controller based on online system identification using quantum-behaved particle swarm optimization. Soft Comput 19, 1715–1725 (2015). https://doi.org/10.1007/s00500-014-1359-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-014-1359-9

Keywords