Advertisement

QoS-aware service composition for cloud manufacturing based on the optimal construction of synergistic elementary service groups

  • Bo Liu
  • Zili Zhang
ORIGINAL ARTICLE

Abstract

Cloud manufacturing (CMfg) has drawn extensive attentions from industrial community and academia. Quality of service (QoS)-aware service composition is critical to the on-demand use of distributed manufacturing resources and capabilities in CMfg systems. However, most previous work plainly composed composite services by the approach of one-to-one mapping-based service composition (OOM-SC), which leads to drawbacks to both the overall QoS of composite services and the success rate of service composition. To circumvent this, an approach of synergistic elementary service group-based service composition (SESG-SC) is proposed in this paper. It releases the assumption of one-to-one mapping between elementary services and subtasks, allowing a free combination of multiple functionally equivalent elementary services into a synergistic elementary service group (SESG) to perform each subtask collectively, thereby bettering the overall QoS and achieving more acceptable success rate. To introduce an optimal construction of SESGs into the optimization model of QoS-aware service composition, three kinds of redundant structures within SESGs are discussed and the corresponding QoS evaluation formulas are also proposed. To deal with the increasing computing complexity of the optimization model, an algorithm named matrix-coded genetic algorithm with collaboratively evolutional populations (MCGA-CEP) is designed in the current study. The experimental results indicate that the proposed SESG-SC approach significantly outperforms the previous approaches, and the proposed MCGA-CEP is sound on performance-wise.

Keywords

Cloud manufacturing (CMfg) Service composition Quality of service (QoS) Synergistic elementary service group (SESG) Genetic algorithm 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Li B, Zhang L, Wang S, Tao F, Cao J, Jiang X, Song X, Chai X (2010) Cloud manufacturing: a new service-oriented networked manufacturing model. Comput Integr Manuf Syst 16(1):1–7Google Scholar
  2. 2.
    Zhong RY, Lan S, Xu C, Dai Q, Huang GQ (2016) Visualization of RFID-enabled shopfloor logistics big data in cloud manufacturing. Int J Adv Manuf Technol 84(1):5–16CrossRefGoogle Scholar
  3. 3.
    Zhang Y, Xi D, Li R, Sun S (2016) Task-driven manufacturing cloud service proactive discovery and optimal configuration method. Int J Adv Manuf Technol 84(1):29–45CrossRefGoogle Scholar
  4. 4.
    Dubey R, Gunasekaran A (2015) Agile manufacturing: framework and its empirical validation. Int J Adv Manuf Technol 76(9):2147–2157CrossRefGoogle Scholar
  5. 5.
    Ren L, Cui J, Wei Y, LaiLi Y, Zhang L (2016) Research on the impact of service provider cooperative relationship on cloud manufacturing platform. Int J Adv Manuf Technol. doi: 10.1007/s00170-016-8345-6 Google Scholar
  6. 6.
    Tao F, Hu YF, Zhou ZD (2008) Study on manufacturing grid & its resource service optimal-selection system. Int J Adv Manuf Technol 37(9):1022–1041CrossRefGoogle Scholar
  7. 7.
    Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput Integr Manuf 28(1):75–86CrossRefGoogle Scholar
  8. 8.
    Wang C, Bi Z, Xu LD (2014) IoT and cloud computing in automation of assembly modeling systems. IEEE Trans Ind Inf 10(2):1426–1434Google Scholar
  9. 9.
    Tao F, Zhang L, Lu K, Zhao D (2012) Research on manufacturing grid resource service optimal-selection and composition framework. Int J Enterp Inf Syst 6(2):237–264CrossRefGoogle Scholar
  10. 10.
    Tao F, Cheng Y, Da Xu L, Zhang L, Li B (2014) CCIoT-CMfg: cloud computing and Internet of things-based cloud manufacturing service system. IEEE T Ind Inform 10(2):1435–1442CrossRefGoogle Scholar
  11. 11.
    Tao F, Wang Y, Zuo Y, Yang H, Zhang M (2016) Internet of things in product life-cycle energy management. J Ind Inf Integ. doi: 10.1016/j.jii.2016.03.001 Google Scholar
  12. 12.
    Xu LD, He W, Li S (2014) Internet of things in industries: a survey. IEEE Trans Ind Inf 10(4):2233–2243CrossRefGoogle Scholar
  13. 13.
    Li S, Xu LD, Zhao S (2015) The internet of things: a survey. Inf Syst Front 17(2):243–259CrossRefGoogle Scholar
  14. 14.
    Cai H, Xu LD, Xu B, Xie C, Qin S, Jiang L (2014) IoT-based configurable information service platform for product lifecycle management. IEEE Trans Ind Inf 10(2):1558–1567CrossRefGoogle Scholar
  15. 15.
    Bi Z, Xu LD, Wang C (2014) Internet of things for enterprise systems of modern manufacturing. IEEE Trans Ind Inf 10(2):1537–1546CrossRefGoogle Scholar
  16. 16.
    Liu Z, Wang Y, Cai L, Cheng Q, Zhang H (2016) Design and manufacturing model of customized hydrostatic bearing system based on cloud and big data technology. Int J Adv Manuf Technol 84(1):261–273CrossRefGoogle Scholar
  17. 17.
    Chen Y, Chen H, Gorkhali A, Lu Y, Ma Y, Li L (2016) Big data analytics and big data science: a survey. J Manag Analyt 3(1):1–42CrossRefGoogle Scholar
  18. 18.
    Chong D, Shi H (2015) Big data analytics: a literature review. J Manag Analyt 2(3):175–201CrossRefGoogle Scholar
  19. 19.
    Tao F, LaiLi Y, Xu L, Zhang L (2013) FC-PACO-RM: a parallel method for service composition optimal-selection in cloud manufacturing system. IEEE T Ind Inform 9(4):2023–2033CrossRefGoogle Scholar
  20. 20.
    Li B, Zhang L, Ren L, Chai X, Tao F, Luo Y, Wang Y, Yin C, Huang G, Zhao X (2011) Further discussion on cloud manufacturing. Comput Integr Manuf Syst 17(3):449–457Google Scholar
  21. 21.
    Zhang L, Luo Y, Tao F, Li B, Ren L, Zhang X, Guo H, Cheng Y, Hu A, Liu Y (2014) Cloud manufacturing: a new manufacturing paradigm. Int J Enterp Inf Syst 8(2):167–187CrossRefGoogle Scholar
  22. 22.
    Tao F, Zhao D, Hu Y, Zhou Z (2008) Resource service composition and its optimal-selection based on particle swarm optimization in manufacturing grid system. IEEE T Ind Inform 4(4):315–327CrossRefGoogle Scholar
  23. 23.
    Xu LD (2011) Enterprise systems: state-of-the-art and future trends. IEEE Trans Ind Inf 7(4):630–640CrossRefGoogle Scholar
  24. 24.
    Viriyasitavat W (2016) Multi-criteria selection for services selection in service workflow. J Ind Inf Integ. doi: 10.1016/j.jii.2016.03.003 Google Scholar
  25. 25.
    Liu W, Liu B, Sun D, Li Y, Ma G (2013) Study on multi-task oriented services composition and optimisation with the ‘multi-composition for each task’ pattern in cloud manufacturing systems. Int J Comput Integr Manuf 26(8):786–805CrossRefGoogle Scholar
  26. 26.
    He W, Xu LD (2015) A state-of-the-art survey of cloud manufacturing. Int J Comput Integr Manuf 28(3):239–250CrossRefGoogle Scholar
  27. 27.
    Tao F, Zuo Y, Xu LD, Zhang L (2014) IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans Ind Inf 10(2):1547–1557CrossRefGoogle Scholar
  28. 28.
    Tao F, Zhang L, Liu Y, Cheng Y, Wang L, Xu X (2015) Manufacturing service management in cloud manufacturing: overview and future research directions. J Manuf Sci E-T Asme 137(4):040912CrossRefGoogle Scholar
  29. 29.
    Qu T, Lei SP, Wang ZZ, Nie DX, Chen X, Huang GQ (2016) IoT-based real-time production logistics synchronization system under smart cloud manufacturing. Int J Adv Manuf Technol 84(1):147–164CrossRefGoogle Scholar
  30. 30.
    Fan W, Xiao T (2011) Integrated architecture of cloud manufacturing based on federation mode. Comput Integr Manuf Syst 17(3):469–476Google Scholar
  31. 31.
    Ma C, Ren L, Teng D, Wang H, Dai G (2011) Ubiquitous human-computer interaction in cloud manufacturing. Comput Integr Manuf Syst 17(3):504–510Google Scholar
  32. 32.
    Ren L, Zhang L, Zhang Y, Tao F, Luo Y (2011) Resource virtualization in cloud manufacturing. Comput Integr Manuf Syst 17(3):511–518Google Scholar
  33. 33.
    Yin C, Huang B, Liu F, Wen L, Wang Z, Li X, Yang S, Ye D, Liu X (2011) Common key technology system of cloud manufacturing service platform for small and medium enterprises. Comput Integr Manuf Syst 17(3):495–503Google Scholar
  34. 34.
    Zhang L, Luo Y, Tao F, Ren L, Guo H (2010) Key technologies for the construction of manufacturing cloud. Comput Integr Manuf Syst 16(11):2510–2520Google Scholar
  35. 35.
    Yin S, Yin C, Liu F, Li X (2011) Outsourcing resources integration service mode and semantic description in cloud manufacturing environment. Comput Integr Manuf Syst 17(3):525–532Google Scholar
  36. 36.
    Zhang Q, Qi D (2011) Service-oriented collaborative design platform for cloud manufacturing. J South China Univ Technol (Natural Science) 39(12):75–81Google Scholar
  37. 37.
    Ren L, Zhang L, Tao F, Zhao C, Chai X, Zhao X (2015) Cloud manufacturing: from concept to practice. Int J Enterp Inf Syst 9(2):186–209CrossRefGoogle Scholar
  38. 38.
    Ardagna D, Pernici B (2007) Adaptive service composition in flexible processes. IEEE T Software Eng 33(6):369–384CrossRefGoogle Scholar
  39. 39.
    Guo H, Tao F, Zhang L, Su S, Si N (2010) Correlation-aware Web services composition and QoS computation model in virtual enterprise. Int J Adv Manuf Technol 51:817–827CrossRefGoogle Scholar
  40. 40.
    Zhang H, Hu Y (2011) A hybrid chaotic quantum evolutionary algorithm for resource combinatorial optimization in manufacturing grid system. Int J Adv Manuf Technol 52:821–831CrossRefGoogle Scholar
  41. 41.
    Wang ZJ, Liu ZZ, Zhou XF (2011) An approach for composite Web service selection based on DGQoS. Int J Adv Manuf Technol 56(9–12):1167–1179CrossRefGoogle Scholar
  42. 42.
    Huang B, Li C, Tao F (2014) A chaos control optimal algorithm for QoS-based service composition selection in cloud manufacturing system. Int J Enterp Inf Syst 8(4):445–463CrossRefGoogle Scholar
  43. 43.
    Cao Y, Wang S, Kang L, Gao Y (2015) A TQCS-based service selection and scheduling strategy in cloud manufacturing. Int J Adv Manuf Technol. doi: 10.1007/s00170-015-7350-5 Google Scholar
  44. 44.
    Zeng L, Benatallah B, Ngu AHH, Dumas M, Kalagnanam J, Chang H (2004) QoS-aware middleware for Web services composition. IEEE T Software Eng 30(5):311–327CrossRefGoogle Scholar
  45. 45.
    Cardoso J, Sheth A, Miller J, Arnold J, Kochut K (2004) Quality of service for workflows and Web service processes. J Web Semant 1(2004):281–308CrossRefGoogle Scholar
  46. 46.
    Zeng J, Sun H, Liu X, Deng T, Huai J (2010) Dynamic evolution mechanism for trustworthy software based on service composition. Int J Softw 21(2):261–276CrossRefGoogle Scholar
  47. 47.
    Menasce DA (2002) QoS issues in Web services. IEEE Internet Comput 6(6):72–75CrossRefGoogle Scholar
  48. 48.
    Li J, Zhao Y, Sun H, Zheng Z, Ma D (2011) DH4SS: a distributed heuristic for QoS-based service selection. Int J Web Grid Serv 7(4):388–409CrossRefGoogle Scholar
  49. 49.
    Alrifai M, Risse T, Nejdl W (2012) A hybrid approach for efficient Web service composition with end-to-end QoS constraints. ACM T Web 6(2):7:1–7:31Google Scholar
  50. 50.
    Richter J, Baruwal Chhetri M, Kowalczyk R, Bao VQ (2012) Establishing composite SLAs through concurrent QoS negotiation with surplus redistribution. Concurr Comp-Pract E 24(9):938–955CrossRefGoogle Scholar
  51. 51.
    Liu ZZ, Xue X, Shen JQ, Li WR (2013) Web service dynamic composition based on decomposition of global QoS constraints. Int J Adv Manuf Technol 69(9–12):2247–2260CrossRefGoogle Scholar
  52. 52.
    Lin C, Sheu RK, Chang Y, Yuan S (2011) A relaxable service selection algorithm for QoS-based Web service composition. Inf Softw Technol 53(12):1370–1381CrossRefGoogle Scholar
  53. 53.
    He Q, Yan J, Jin H, Yang Y (2014) Quality-aware service selection for service-based systems based on iterative multi-attribute combinatorial auction. IEEE T Software Eng 40(2):192–215CrossRefGoogle Scholar
  54. 54.
    Ko JM, Kim CO, Kwon IH (2008) Quality-of-service oriented Web service composition algorithm and planning architecture. J Syst Softw 81(11):2079–2090CrossRefGoogle Scholar
  55. 55.
    Li F, Xu LD, Jin C, Wang H (2012) Random assignment method based on genetic algorithms and its application in resource allocation. Expert Syst Appl 39(15):12213–12219CrossRefGoogle Scholar
  56. 56.
    Li F, Xu LD, Jin C, Wang H (2011) Intelligent bionic genetic algorithm (IB-GA) and its convergence. Expert Syst Appl 38(7):8804–8811CrossRefGoogle Scholar
  57. 57.
    Li F, Xu LD, Jin C, Wang H (2011) Structure of multi-stage composite genetic algorithm (MSC-GA) and its performance. Expert Syst Appl 38(7):8929–8937CrossRefGoogle Scholar
  58. 58.
    Ma Y, Zhang C (2008) Quick convergence of genetic algorithm for QoS-driven Web service selection. Comput Netw 52(5):1093–1104CrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  1. 1.Faculty of Computer and Information ScienceSouthwest UniversityChongqingChina

Personalised recommendations