JACIII Vol.15 No.4 pp. 400-405
doi: 10.20965/jaciii.2011.p0400


Next Generation Passive Optical Networking Technology Predictions by Using Hybrid MCDM Methods

Chi-Yo Huang*1, Shih-Yu Chang*2, Yu-Hsien Yang*2,
and Gwo-Hshiung Tzeng*3,*4

*1Department of Industrial Education, National Taiwan Normal University, No.162, Section 1, He-ping East Road, Taipei 106, Taiwan

*2Dept. of Computer Science, National Tsing Hua University, No.101, Section 2, Kuang Fu Road, Hsinchu, Taiwan

*3Institute of Project Management, Kainan University, No.1 Kainan Road, Luchu, Taoyuan 338, Taiwan

*4Institute of Management of Technology, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu 300, Taiwan

January 7, 2011
March 1, 2011
June 20, 2011
technology foresight, multiple criteria decision making (MCDM), telecommunications, networking
The evolution of broadband telecommunication technologies has enabled applications over networks, which, in turn, has enabled the emergence of novel network services and applications such as VoIP and video on demand in triggering demand for higher network bandwidth. Passive Optical Networking (PON) is suitable for eliminating bandwidth insufficiency, so national governments and communities are observing the emergence of Fiber-To-The-Home (FTTH) technologies. Ethernet-based Passive Optical Networks (EPON) and Gigabit-based PON (GPON) are two candidates for next-generation PON in bandwidth efficiency. To predict which is more suitable nationally, we define a foresight framework based on hybrid Multiple Criteria Decision Making (MCDM) methods for selecting the most suitable PON. The development of next-generation PON, including Ethernet PON (EPON) and Gigabit PON (GPON), is introduced and compared. Experts from industry and academia were invited to predict the most suitable next-generation PON for Japan and emerging economies such as Taiwan. Results showed that EPON is most suitable for Japan and GPON most suitable for Taiwan. Results for the technological foresight can serve as the basis for national telecommunication policy and business product definition.
Cite this article as:
C. Huang, S. Chang, Y. Yang, and G. Tzeng, “Next Generation Passive Optical Networking Technology Predictions by Using Hybrid MCDM Methods,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.4, pp. 400-405, 2011.
Data files:
  1. [1] ASTRO Systems Inc., “Telecommunications Development Fund Technical Assistance, Universal Access Program Manual of Operating Procedures,” 2008.
  2. [2] K. S. Kim, “On the evolution of PON-based FTTH solutions,” Information Sciences, Vol.149, pp. 21-30, 2003.
  3. [3] ACTU, “Shareholder risks associated with the National Broadband Network.” (Online) Available:
  4. [4] P. D. Townsend, G. Talli, C. W. Chow, E. M. MacHale, C. Antony, R. Davey, T. D. Ridder, X. Z. Qiu, P. Ossieur, H. G. Krimmel, D. W. Smith, I. Lealman, A. Poustie, S. Randel, and H. Rohde, “Long Reach Passive Optical Networks,” the IEEE LEOS Annual Meeting, 2007.
  5. [5] S. R. Sherif, A. Hadjiantonis, G. Ellinas, C. Assi, and M. A. Ali, “A novel decentralized Ethernet-based PON access architecture for provisioning differentiated QoS,” J. of Lightwave Technology, Vol.22, pp. 2483-2497, 2004.
  6. [6] B. Skubic, J. Chen, J. Ahmed, L. Wosinska, and B. Mukherjee, “A comparison of dynamic bandwidth allocation for EPON, GPON, and next-generation TDM PON,” IEEE Communication Magazine, Vol.47, pp. S40-S48, 2009.
  7. [7] L. Georghiou, “The UK technology foresight programme,” Futures, Vol.28, pp. 359-377, 1996.
  8. [8] B. R.Martin and R. Johnston, “Technology Foresight forWiring Up the National Innovation System: Experiences in Britain, Australia and New Zealand,” Technological Forecasting and Social Change, Vol.60, pp. 37-54, 1999.
  9. [9] W. J. Abernathy and K. B. Clark, “Innovation: Mapping the Winds of Creative Destruction,” Research Policy, Vol.14, pp. 3-22, 1985.
  10. [10] M. E. Porter, “Competitive advantage: creating and sustaining superior performance,” New York, N.Y., Free Press, 1985.
  11. [11] A. Antunes and C. Canongia, “Technological foresight and technological scanning for identifying priorities and opportunities: the biotechnology and health sector,” Foresight, Vol. 8, pp. 31-44, 2006.
  12. [12] K. Cuhls, “From forecasting to foresight processes-New participative foresight activities in Germany,” J. of forecasting, Vol.22, pp. 93-111, 2003.
  13. [13] C.-Y. Huang and G.-H. Tzeng, “Multiple generation product life cycle predictions using a novel two-stage fuzzy piecewise regression analysis method,” Technological Forecasting and Social Change, Vol.75, pp. 12-31, 2008.
  14. [14] P.-F. Pai, W.-C. Hong, and C.-S. Lin, “Forecasting Electric Load by Support Vector Machines with Genetic Algorithms,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.9, pp. 134-141, 2005.
  15. [15] F. Pasila, A. K. Palit, and G. Thiele, “Neuro-Fuzzy Approaches for Forecasting Electrical Load Using Additional Moving Average Window Data Filter on Takagi-Sugeno Type MISO Networks,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.12, pp. 361-369, 2008.
  16. [16] C.-Y. Huang, G.-H. Tzeng, C.-C. Chan, and H.-C. Wu, “Semiconductor Market Fluctuation Indicators and Rules Derivations by using the Rough Set Theory,” Int. J. of Innovative Computing, Information and Control, Vol.5, pp. 1483-1503, 2009.
  17. [17] G. Reger, “Technology Foresight in Companies: From an Indicator to a Network and Process Perspective,” Technology Analysis & Strategic Management, Vol.13, pp. 533-553, 2001.
  18. [18] C. Andriopoulos and M. Gotsi, “Probing the future: Mobilising foresight in multiple-product innovation firms,” Futures, Vol.38, pp. 50-66, 2005.
  19. [19] J. Prat, P. Chanclou, R. Davey, J. M. Finochietto, G. Franzl, A. M. J. Koonen, and S. Walker, “Long-term Evolution of Passive Optical Networks,” in the 1st Int. Conf. on Access networks, 2006.
  20. [20] D. Parsons, “GPON vs. EPON: a cost comparison (gigabit passive optical network, broadband passive optical network),” in Lightwave, PennWell Publishing, 2005.
  21. [21] C.-Y. Huang, Y.-H. Hung, and G.-H. Tzeng, “Using Hybrid MCDM Methods to Assess Fuel Cell Technology for the Next Generation of Hybrid Power Automobiles,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.15, No.4, pp. 406-417, 2011.

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