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This paper introduces a model for optimizing Fiber-to-the-Home (FTTH) access networks, focusing on market share, quality of service levels, operator strategies, and user willingness to pay. It includes a clustering process and two-stage optimization models to enhance FTTH network performance and profitability.
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A Network Economic Strategy Model For FTTH Access Network YANG MING-5120309656
Outline Introduction of FTTH Motivation Problem Formulation Optimization Process Stage 1 Optimization Model Stage 2 Optimization Model Simulation Result Reference Q&A
FTTH what is FTTH(光纤入户) FTTH is the abbreviation of fiber to the home FTTH refers to the optical network unit (ONU) installed in the home user or business user FTTH is the closest type of optical access application network to the user except FTTD in the optical access series
Problem Formulation NO YES
background of the model FTTH market share among K FTTH players,operator k={1,...,K} serviceat level of QoS l where l = {1,...,L},level 1 is the worst,level L is the best I users in the market,user i = {1,...,I} user groupsJ,group j ={1,...,J} Hk is the number of home passed of operator k,Hk is constant
Clustering Process clustering process groups I users into J user groups at initial time k-means algorithm is used and only use the willingness as the parameter for clustering process A demonstration of the algorithm
input and output from clustering input the amount of user group J willingness of user i to pay for level l service at time t wi,l(t) output from clustering willingness to pay of user group j for service level l at time t,wj,l(t) the user group that user i participated for a service level l,gi,l(t)
Optimization process input user status user status of other operator maximum bandwich amount of user in group j the number of new user in group j newuser status of operator k
Stage 1 optimization model aj,k,l(t) the user group status pk,l(t) the monthly tariff
Stage 1 optimization model Rk,l(t) need to subject to some requirement:
Stage 1 optimization model update the user status: amount of users adopt l level service the number of OLTs Ok,l(t) need to subject to:
Stage 1 optimization model the number of OLTs Ok,l(t): the stage 1 optimization model optimize the optimum user groups that operator k should service and theoptimum tariff with QoS level l
Stage 2 optimization model the stage 2 optimization model need to optimizes the level of QoS of operator k the output of stage 1 Pk,l(t) is input of stage 2 the model is formulated: subject to :
Stage 2 optimization model update the number of OLTs update the new user status user status of other operator new user status of the operator at time t
Simulation Results the parameter table:
Simulation Results A comparison of cumulative profit of both operators. A comparison of profit of operators at the instant time t
Simulation Results A comparison of tariff of operators at the instant time t A comparison level of QoS of the operators at the instant time t.
Simulation Results A comparison of the amount of home connected of the operators atinstant time t
Reference M. Khil and et.al. "Traffic analysis and characterization of Internet user behavior," in Proc. ICUMT, Oct. 2010, pp. 224-231 P. Rappoport and J. Alleman. "Modeling Demand for TelecomServices Using Surveys", Geneva, Switzerland, Oct. 2004. G. Rosston, S.J. Savage and D. Waldman. "Household Demand for Broadband Internet Service," Communications of the ACM, Vol.54, pp. 29-31, Feb. 2011.
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