Quality of service in manufacturing networks: a service framework and its implementation

  • Wenjun Xu
  • Zude Zhou
  • D. T. Pham
  • Quan Liu
  • C. Ji
  • Wei Meng


Due to the continuous growth in the application of networks in manufacturing, quality of service (QoS) has become an important issue. In this paper, the concept of QoS for manufacturing networks is discussed. To provide overall performance assurance for manufacturing networks, a service framework integrating the QoS mechanisms of the networked resource service management function and the communication networks is proposed. The novel framework maps an application to resource services and then to communication networks, adopts an intelligent optimisation algorithm for QoS management of resource services, and provides QoS schemes for data transfer across communication networks. A prototype implementation has been realised and a set of simulation experiments conducted to evaluate the validity of the framework. The results obtained demonstrate the ability of the framework to satisfy the various performance requirements posed by such applications and provide efficient overall performance assurance for manufacturing networks.


Manufacturing networks Quality of service Networked resource service management Bees algorithm Communication networks 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    EC (2009) Final Future Internet Enterprise Systems (FInES) cluster position paperGoogle Scholar
  2. 2.
    Camarinha-Matos LM, Afsarmanesh H, Galeano N, Molina A (2009) Collaborative networked organizations—concepts and practice in manufacturing enterprises. Comput Ind Eng 57(1):46–60CrossRefGoogle Scholar
  3. 3.
    Camarinha-Matos LM (2009) Collaborative networked organizations: status and trends in manufacturing. Annu Rev Control 33(2):199–208CrossRefGoogle Scholar
  4. 4.
    Qiu RG (2004) Manufacturing grid: a next generation manufacturing model. In: IEEE International Conference on Systems, Man and Cybernetics, The Hague, NetherlandsGoogle Scholar
  5. 5.
    Tao F, Hu Y, Zhou Z (2008) Study on manufacturing grid and its resource service optimal-selection system. Int J Adv Manuf Technol 37(9–10):1022–1041CrossRefGoogle Scholar
  6. 6.
    Li Z, Jin X, Cao Y, Zhang X, Li Y (2007) Conception and implementation of a collaborative manufacturing grid. Int J Adv Manuf Technol 34(11–12):1224–1235CrossRefGoogle Scholar
  7. 7.
    Shi SY, Mo R, Yang HC, Chang ZY, Chen ZF (2007) An implementation of modelling resource in a manufacturing grid for resource sharing. Int J Comput Integr Manuf 20(2–3):169–177CrossRefGoogle Scholar
  8. 8.
    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 Trans Ind Informatics 4(4):315–327CrossRefGoogle Scholar
  9. 9.
    Hu H, Li Z (2009) Modeling and scheduling for manufacturing grid workflows using timed Petri nets. Int J Adv Manuf Technol 42(5–6):553–568CrossRefGoogle Scholar
  10. 10.
    Weiss A (2007) Computing in the clouds. netWorker 11(4):16–25CrossRefGoogle Scholar
  11. 11.
    Huynh SX, Quan DA (2008) Cloud computing in manufacturing environment. In: AIChE Spring National Meeting, New Orleans, LA, USAGoogle Scholar
  12. 12.
    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
  13. 13.
    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
  14. 14.
    Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput Integr Manuf 28(1):75–86CrossRefGoogle Scholar
  15. 15.
    Zhou Z, Liu Q, Xu W (2011) From digital manufacturing to cloud manufacturing. Int J Eng Innov Manag 1(1):1–14Google Scholar
  16. 16.
    Li B, Zhang L, Chai X (2010) Introduction to cloud manufacturing. ZTE Commun 8(4):6–9Google Scholar
  17. 17.
    Zhang L, Luo Y, Tao F, Ren L, Guo H (2011) Key technologies for the construction of manufacturing cloud. Comput Integr Manuf Syst 16(11):2510–2520Google Scholar
  18. 18.
    Fan Y, Zhang L, Liu B (2004) Networked manufacturing and manufacturing network. China Mech Eng 15(19):1733–1738Google Scholar
  19. 19.
    Zhang JB, Ng BTJ, Wong MM, Zhuang LQ (2005) Manufacturing service negotiation and resource management: a QoS approach. In: 5th International Conference on Control and Automation, ICCA'05, Guangzhou, ChinaGoogle Scholar
  20. 20.
    Moyne JR, Tilbury DM (2007) The emergence of industrial control networks for manufacturing control, diagnostics, and safety data. Proc IEEE 95(1):29–47CrossRefGoogle Scholar
  21. 21.
    Lian FL, Moyne JR, Tilbury DM (2001) Performance evaluation of control networks: Ethernet, ControlNet, and DeviceNet. IEEE Control Syst Mag 21(1):66–83CrossRefGoogle Scholar
  22. 22.
    Soucek S, Sauter T (2004) Quality of service concerns in IP-based control systems. IEEE Trans Ind Electron 51(6):1249–1258CrossRefGoogle Scholar
  23. 23.
    Pedreiras P, Gai P, Almeida L, Buttazzo GC (2005) FTT-Ethernet: a flexible real-time communication protocol that supports dynamic QoS management on Ethernet-based systems. IEEE Trans Ind Informa 1(3):162–172CrossRefGoogle Scholar
  24. 24.
    Skeie T, Johannessen S, Holmeide O (2006) Timeliness of real-time IP communication in switched industrial Ethernet networks. IEEE Trans Ind Informa 2(1):25–39CrossRefGoogle Scholar
  25. 25.
    Cuong DM, Kim MK (2007) Real-time communications on an integrated fieldbus network based on a switched Ethernet in industrial environment. Lect Notes Comput Sci 4523(2007):498–509CrossRefGoogle Scholar
  26. 26.
    Gunasekaran A, Love PED (1999) A review of multimedia technology in manufacturing. Comput Ind 38(1):65–76CrossRefGoogle Scholar
  27. 27.
    Sempere VM, Silvestre J (2003) Multimedia applications in industrial networks: integration of image processing in Profibus. IEEE Trans Ind Electron 50(3):440–448CrossRefGoogle Scholar
  28. 28.
    Silvestre J, Almeida L, Marau R, Pedreiras P (2007) Dynamic QoS management for multimedia real-time transmission in industrial environments. In: IEEE Symposium on Emerging Technologies and Factory Automation, ETFA, Patras, GreeceGoogle Scholar
  29. 29.
    Lee SH, Cho KH (2001) Congestion control of high-speed Gigabit-Ethernet networks for industrial applications. In: IEEE International Symposium on Industrial Electronics, Pusan, KoreaGoogle Scholar
  30. 30.
    Foster I, Kesselman C, Lee C, Lindell B, Nahrstedt K, Roy A (1999) A distributed resource management architecture that supports advanced reservations and co-allocation. In: 7th International Workshop on Quality of Service, London, UKGoogle Scholar
  31. 31.
    Al-Ali RJ, Rana OF, Walker DW, Jha S, Sohail S (2002) G-QoSM: grid service discovery using QoS properties. Comput Inf J 21(4):363–382zbMATHGoogle Scholar
  32. 32.
    Tao F, Hu Y, Zhao D, Zhou Z, Zhang H, Lei Z (2009) Study on manufacturing grid resource service QoS modeling and evaluation. Int J Adv Manuf Technol 41(9–10):1034–1042CrossRefGoogle Scholar
  33. 33.
    Shi Z, Yu T, Liu L (2004) MG-QoS: QoS-based resource discovery in manufacturing grid. In: Lecture Notes in Computer Science. pp. 500–506Google Scholar
  34. 34.
    Sun H, Yu T, Liu L, He Y (2006) QoS management in manufacturing grid. In: IFIP International Federation for Information Processing. pp. 831–839Google Scholar
  35. 35.
    Tao F, Hu Y, Zhou Z (2009) Application and modeling of resource service trust-QoS evaluation in manufacturing grid system. Int J Prod Res 47(6):1521–1550CrossRefGoogle Scholar
  36. 36.
    Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I (2009) Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Futur Gener Comput Syst 25(6):599–616CrossRefGoogle Scholar
  37. 37.
    Stantchev V, Schropfer C (2009) Negotiating and enforcing QoS and SLAs in grid and cloud computing. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 25–35Google Scholar
  38. 38.
    Xu M, Cui L, Wang H, Bi Y (2009) A multiple QoS constrained scheduling strategy of multiple workflows for cloud computing. In: IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2009, Chengdu and Jiuzhai Valley, ChinaGoogle Scholar
  39. 39.
    Cao BQ, Li B, Xia QM (2009) A service-oriented Qos-assured and multi-agent cloud computing architecture. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 644–649Google Scholar
  40. 40.
    Manuel PD, Thamarai Selve S, Barr MIAEI (2009) Trust management system for grid and cloud resources. In: 1st International Conference on Advanced Computing, ICAC 2009, Chennai, IndiaGoogle Scholar
  41. 41.
    Li W, Ping L (2009) Trust model to enhance security and interoperability of cloud environment. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 69–79Google Scholar
  42. 42.
    Krautheim FJ, Phatak DS, Sherman AT (2010) Introducing the trusted virtual environment module: a new mechanism for rooting trust in cloud computing. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 211–227Google Scholar
  43. 43.
    Miras D (2002) A survey of network QoS needs of advanced Internet applications. Working Paper, Internet2 QoS Working Group. University College, LondonGoogle Scholar
  44. 44.
    Sabata B, Chatterjee S, Davis M, Sydir JJ, Lawrence TF (1997) Taxonomy for QoS specifications. In: Workshop on Object-Oriented Real-Time Dependable Systems, WORDS'07, Capri Island, ItalyGoogle Scholar
  45. 45.
    Bonabeau E, Dorigo M, Theraulaz G (1999) Swarm intelligence: from natural to artificial systems. Oxford University Press, New YorkzbMATHGoogle Scholar
  46. 46.
    Goldberg DE (1989) Algorithms in search, optimization and machine learning. Addison-Wesley Professional, ReadingzbMATHGoogle Scholar
  47. 47.
    Dorigo M, Di Caro G, Gambardella LM (1999) Ant algorithms for discrete optimization. Artif Life 5(2):137–172CrossRefGoogle Scholar
  48. 48.
    Kennedy J, Eberhart R (1995) Particle swarm optimization. In: IEEE International Conference on Neural Networks (ICNN'95), Perth, AustraliaGoogle Scholar
  49. 49.
    Pham DT, Ghanbarzadeh A, Koç E, Otri S, Rahim S, Zaidi M (2006) The bees algorithm—a novel tool for complex optimisation problems. In: Innovative Production Machines and Systems, IPROMS'06, Cardiff, UKGoogle Scholar
  50. 50.
    Pham DT, Castellani M (2009) The bees algorithm: modelling foraging behaviour to solve continuous optimization problems. Proc Inst Mech Eng Part C: J Mech Eng Sci 223(12):2919–2938CrossRefGoogle Scholar
  51. 51.
    Pham DT, Afify A, Koc E (2007) Manufacturing cell formation using the bees algorithm. In: Innovative Production Machines and Systems, IPROMS'07, Cardiff, UKGoogle Scholar
  52. 52.
    Pham DT, Koc E, Lee JY, Phrueksanant J (2007) Using the bees algorithm to schedule jobs for a machine. In: 8th International Conference on Laser Metrology, CMM and Machine Tool Performance, LAMDAMAP'07, Cardiff, UKGoogle Scholar
  53. 53.
    Pham DT, Ghanbarzadeh A, Otri S, Koc E (2009) Optimal design of mechanical components using the bees algorithm. Proc Ins Mech Eng Part C: J Mech Eng Sci 223(5):1051–1056CrossRefGoogle Scholar
  54. 54.
    Pham DT, Castellani M, Fahmy AA (2008) Learning the inverse kinematics of a robot manipulator using the bees algorithm. In: IEEE International Conference on Industrial Informatics, INDIN 2008, Daejeon, KoreaGoogle Scholar
  55. 55.
    Hafid A, Bochmann GV (1998) Quality-of-service adaptation in distributed multimedia applications. Multimedia Systems 6(5):299–314CrossRefGoogle Scholar
  56. 56.
    Pham DT, Ghanbarzadeh A (2007) Multi-objective optimisation using the bees algorithm. In: Innovative Production Machines and Systems, IPROMS'07, Cardiff, UKGoogle Scholar
  57. 57.
    Truong HL, Samborski R, Fahringer T (2006) Towards a framework for monitoring and analyzing QoS metrics of grid services. In: 2nd IEEE International Conference on e-Science and Grid Computing, e-Science'06, Amsterdam, NetherlandsGoogle Scholar
  58. 58.
    Al-Ali RJ (2005) Quality of service management in service-oriented grids. PhD thesis, Cardiff UniversityGoogle Scholar
  59. 59.
    Lee S, Lee SH, Lee KC, Lee MH, Harashima F (2001) Intelligent performance management of networks for advanced manufacturing systems. IEEE Trans Ind Electron 48(4):731–741CrossRefGoogle Scholar
  60. 60.
    USC/ISI (2010) The NS simulator. Available at: Accessed Jan 2010
  61. 61.
    Zhou Z, Xu W, Pham DT, Ji C (2009) QoS modeling and analysis for manufacturing networks: a service framework. In: 7th IEEE International Conference on Industrial Informatics, INDIN 2009, Cardiff, UKGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  • Wenjun Xu
    • 1
  • Zude Zhou
    • 1
  • D. T. Pham
    • 2
  • Quan Liu
    • 1
  • C. Ji
    • 3
  • Wei Meng
    • 1
  1. 1.School of Information EngineeringWuhan University of TechnologyWuhanChina
  2. 2.School of Mechanical EngineeringUniversity of BirminghamBirminghamUK
  3. 3.School of EngineeringCardiff UniversityCardiffUK

Personalised recommendations