Analytical study of retrial / redial phenomena on communication networks with Monte Carlo Simulation

• Main Authors: AnTai Wang, 王安台
• Other Authors: 劉宗平
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/47314109238850602866

博士 === 元智大學 === 電機工程學系 === 99 === Practical customer behaviors for dialing a call include a fresh (new) call, a hand-off call, and a retrial (repeated attempt) call. In analytical models, these behaviors generally were studied by use of a data warehouse of network switches collected and established by the telephone company. The distribution of the arrival and service rates in their models are fixed and limited. In our model based on Monte Carlo method, the random generator was used to produce a value as an initial input data. To mimic real world, the blocking probability, the queueing length, and the waiting time were examined for several cases with different arrival and service rates. In our simulations, the birth-death process and Markov process in queue theory were utilized. Through simulations, we found that the values of the queueing length and the waiting time would be strongly influenced by the variation of the arrival rate. Although the times, in Markovian processes, such as arrival time, service time, and retrial time, can be varied, the stochastic of random variables needed to be considered to obey negative exponential distribution functions with constant averages. However, most distribution functions in problems are not negative exponential in the real world. Therefore, some conclusions deduced from Markovian processes were needed to be justified by some other means. Actually, all methods, such as M/M/1, exponential distribution, Markovian property, used in the whole simulation model, still emphasis the memoryless property. To solve these problems, Monte Carlo method can be the candidate to construct a reasonable model to simulate and analyze the real problem without the assumptions made in the analytical model.