Skip to main content
SpringerLink
Log in

QoS-aware web service selection with negative selection algorithm

  • Regular Paper
  • Published:
Knowledge and Information Systems Aims and scope Submit manuscript

Abstract

Web service selection, as an important part of web service composition, has direct influence on the quality of composite service. Many works have been carried out to find the efficient algorithms for quality of service (QoS)-aware service selection problem in recent years. In this paper, a negative selection immune algorithm (NSA) is proposed, and as far as we know, this is the first time that NSA is introduced into web service selection problem. Domain terms and operations of NSA are firstly redefined in this paper aiming at QoS-aware service selection problem. NSA is then constructed to demonstrate how to use negative selection principle to solve this question. Thirdly, an inconsistent analysis between local exploitation and global planning is presented, through which a local alteration of a composite service scheme can transfer to the global exploration correctly. It is a general adjusting method and independent to algorithms. Finally, extensive experimental results illustrate that NSA, especially for NSA with consistency weights adjusting strategy (NSA+), significantly outperforms particle swarm optimization and clonal selection algorithm for QoS-aware service selection problem. The superiority of NSA+ over others is more and more evident with the increase of component tasks and related candidate services.

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

Access this article

Log in via an institution

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
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Ai LF, Tang ML, Fidge C (2011) Partitioning composite web services for decentralized execution using a genetic algorithm. Future Gener Comput Syst 27:157–172

    Article  Google Scholar 

  2. Alonso G, Casati F, Kuno H, Machiraju V (2003) Web services. Springer, Berlin

    Google Scholar 

  3. Ardagna D, Pernici B (2007) Adaptive service composition in flexible processes. IEEE Trans Softw Eng 33(6):369–384

    Article  Google Scholar 

  4. Berbner R, Spahn M, Repp N et al (2006) Heuristics for QoS-aware web service composition. In: IEEE international conference on web services (ICWS06)

  5. Blau B, Conte T (2011) Contracting co-opetitive in service value networks. In: 2011 IEEE conference on commerce and enterprise, computing, pp 173–178

  6. Blau B, Krämer J, Conte T, van Dinther C (2009) Service value networks. In: 2009 IEEE conference on commerce and enterprise computing, pp 194–201

  7. Chan WKV, Hsu C (2012) Service value networks: humans hypernetwork to cocreate value. IEEE Trans Syst Man Cybern A Syst Hum 42(4):802–913

    Article  MathSciNet  Google Scholar 

  8. Chen BL (2006) Optimization theory and algorithm, 2nd edn. Tsinghua University Press, Beijing

    Google Scholar 

  9. Cao XB, Qiao H, Xu YW (2007) Negative selection based immune optimization. Adv Eng Softw 38:649–656

    Article  Google Scholar 

  10. Das S, Suganthan PN (2011) Differential evolution: a survey of the state-of-the-art. IEEE Trans Evol Comput 15(1):4–31

    Article  Google Scholar 

  11. Dasgupta D, Yu S, Nino F (2011) Recent advances in artificial immune systems: models and applications. Appl Soft Comput 11:1574–1587

    Article  Google Scholar 

  12. de Castro LN, Timmis JI (2002) Artificial immune systems: a new vomputational intelligence paradigm. Springer, Berlin

    Google Scholar 

  13. de Castro LN, von Zuben FJ (2002) Learning and optimization using the clonal selection principle. IEEE Trans Evol Comput 6(3):239–251

    Article  Google Scholar 

  14. De Jong KA (2007) Evolutionary computation: a unified approach. The MIT Press, Cambridge, MA

    Google Scholar 

  15. Di XF, Fan YS, Shen YM (2011) Local martingale difference approach for service selection with dynamic QoS. Comput Math Appl 61(9):2638–2646

    Article  MATH  MathSciNet  Google Scholar 

  16. Fan XQ, Fang XW, Jiang CJ (2011) Research on Web service selection based on cooperative evolution. Expert Syst Appl 38:9736–9743

    Article  Google Scholar 

  17. Haak S, Blau B (2012) Efficient QoS aggregation in service value networks. In: 2012 45th Hawaii international conference on system sciences, pp 1512–1521

  18. Hu CH, Chen XH, Liang XM (2009) Dynamic services selection algorithm in web services composition supporting cross-enterprises collaboration. J Cent South Univ Technol 2:269–274

    Article  Google Scholar 

  19. Kouchakpour P, Zaknich A, Braunl T (2009) A survey and taxonomy of performance improvement of canonical genetic programming. Knowl Inf Syst 21(1):1–39

    Article  Google Scholar 

  20. Laurentys CA, Ronacher G, Palhares RM, Caminhas WM (2010) Design of an artificial immune system for fault detection: a negative selection approach. Expert Syst Appl 37:5507–5513

    Article  Google Scholar 

  21. Liang W-Y, Huang C-C (2009) The generic genetic algorithm incorporates with rough set theory—an application of the web services composition. Expert Syst Appl 36:5549–5556

    Article  Google Scholar 

  22. Luo YS, Qi Y, Hou D et al (2011) A novel heuristic algorithm for QoS-aware end-to-end service composition. Comput Commun 34(9):1137–1144

    Article  Google Scholar 

  23. Ma Y, Zhang CW (2008) Quick convergence of genetic algorithm for QoS-driven web service selection. Comput Netw 52(5):1093–1104

    Article  MATH  Google Scholar 

  24. Menascé DA, Casalicchio E, Dubey V (2010) On optimal service selection in service oriented architectures. Perform Eval 67:659–675

    Article  Google Scholar 

  25. Pop CB, Chifu VR, Salomie I, Dinsoreanu M (2009) Optimal web service composition method based on an enhanced planning graph and using an immune-inspired algorithm. In: IEEE 5th international conference on intelligent computer communication and processing, pp 291–298

  26. Qi LY, Dou WC, Zhang XY, Chen JJ (2012) A QoS-aware composition method supporting cross-platform service invocation in cloud environment. J Comput Syst Sci 78:1316–1329

    Article  MATH  Google Scholar 

  27. Salomie I, Vlad M, Chifu VR, Pop CB (2011) Hybrid immune-inspired method for selecting the optimal or a near-optimal service composition. In: Proceedings of the federated conference on computer science and, information systems, pp 997–1003

  28. Skoutas D, Sacharidis D, Simitsis A, Sellis T (2010) Ranking and clustering web services using multicriteria dominance relationships. IEEE Trans Serv Comput 3(3):163–177

    Article  Google Scholar 

  29. Song S, Lee S-W (2012) A goal-driven approach for adaptive service composition using planning. Math Comput Model. doi:10.1016/j.mcm.2012.08.007

  30. Sun SX, Zhao J (2012) A decomposition-based approach for service composition with global QoS guarantees. Inf Sci 199:138–153

    Article  Google Scholar 

  31. Surace C, Worden K (2010) Novelty detection in a changing environment: a negative selection approach. Mech Syst Signal Process 24:1114–1128

    Article  Google Scholar 

  32. Tsesmetzis D, Roussaki I, Sykas E (2008) QoS-aware service evaluation and selection. Eur J Oper Res 191:1101–1112

    Article  MATH  MathSciNet  Google Scholar 

  33. Wang P, Chao K-M, Lo C-C (2010) On optimal decision for QoS-aware composite service selection. Expert Syst Appl 37:440–449

    Article  Google Scholar 

  34. Wang WB, Sun QB, Yang FC, Zhao XC (2010) An improved particle swarm optimization algorithm for QoS-aware web service selection in service oriented communication. Int J Comput Intell Syst 4(s):18–30

    Article  Google Scholar 

  35. Wang ZJ, Liu ZZ, Zhou XF, Lou YS (2011) An approach for composite web service selection based on DGQoS. Int J Adv Manuf Technol 56:1167–1179

    Article  Google Scholar 

  36. Xiao J, Boutaba R (2005) QoS-aware service composition and adaptation in autonomic communication. IEEE J Sel Areas Commun 23(12):2344–2360

    Article  Google Scholar 

  37. Xu JY, Reiff-Marganiec S (2008) Towards heuristic web services composition using immune algorithm. In: 2008 IEEE international conference on web services, pp 238–245

  38. Yu T, Zhang Y, Lin K-J (2007) Efficient algorithms for web services selection with end-to-end QoS constraints. ACM Trans Web 1(1), Article 6, 26 pages

  39. Zeng LZ, Benatallah B, Ngu Anne HH et al (2004) QoS-aware middleware for web services composition. IEEE Trans Softw Eng 30(5):311–327

    Article  Google Scholar 

  40. Zhan ZH, Zhang J, Li Y et al (2011) Orthogonal learning particle swarm optimization. IEEE Trans Evol Comput 15(6):832–847

    Article  Google Scholar 

  41. Zhao XC, Huang PY, Liu TT, Li XM (2012) A hybrid clonal selection algorithm for quality of service-aware web service selection problem. Int J Innov Comput Inf Control 8(12):8527–8544

    Google Scholar 

  42. Zhao XC, Song BQ, Huang PY et al (2012) An improved discrete immune optimization algorithm based on PSO for QoS-driven web service composition. Appl Soft Comput 12(8):2208–2216

    Article  Google Scholar 

Download references

Acknowledgments

This research is supported by National Natural Science Foundation of China (61105127, 71171079). We will also awfully thank the reviewers’ helpful and constructive comments and suggestions.

Author information

Authors and Affiliations

  1. School of Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Xinchao Zhao

  2. Key Laboratory of Mathematics Mechanization, Institute of Systems Science, AMSS, Chinese Academy of Sciences, Beijing, 100190, China

    Zichao Wen

  3. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210093, China

    Xinchao Zhao

  4. Business Administration School, North China Electric Power University, Beijing, 102206, China

    Xingmei Li

Authors
  1. Xinchao Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zichao Wen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xingmei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xinchao Zhao.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhao, X., Wen, Z. & Li, X. QoS-aware web service selection with negative selection algorithm. Knowl Inf Syst 40, 349–373 (2014). https://doi.org/10.1007/s10115-013-0642-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10115-013-0642-x

Keywords

Search

Navigation