정보처리학회논문지C (The KIPS Transactions:PartC)

한국정보처리학회 (Korea Information Processing Society)
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Synthetic Self-Similar 네트워크 Traffic의 세 가지 고정길이 Sequence 생성기에 대한 비교

A Comparison of Three Fixed-Length Sequence Generators of Synthetic Self-Similar Network Traffic

  • 발행 : 2003.12.01
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초록

최근의 통신 네트워크에서 teletraffic의 양상은 Poisson 프로세스보다 self-similar프로세스에 의해서 더 잘 반영된다. 이는 통신 네트워크의 teletraffic에 관련하여 self-similar한 성질을 고려하지 않는다면, 통신 네트워크의 성능에 관한 결과는 부정확 할 수밖에 없다는 의미가 된다. 따라서, 통신 네트워크에 관한 시뮬레이션을 수행하기 위한 매우 중요한 요소 중에 하나는 충분히 긴 self-similar한 sequence를 얼마나 잘 생성하느냐의 문제이다. 본 논문에서는 FFT〔20〕, RMD〔12〕 그리고 SRA〔5, 10〕 방법을 이용한 세 개의 pseudo-random self-similar sequence 생성기를 비교 분석하였다. 본 Pseudo-random self-similar sequence 생성기의 성질을 매우 긴 sequence를 생성하는데 요구되는 통계적인 정확도와 생성시간에 대해서 분석하였다. 세 개의 pseudo-random self-similar sequence 생성기의 성능은 Hurst 변수의 상대적인 정확도로 보았을 때는 유사했으나, RMD와 SRA 방법을 이용한 pseudo-random self-similar sequence 생성기가 FFT 방법을 이용한 것보다 속도 면에서는 훨씬 빠른 것으로 나타났다. 또한 본 연구를 통해서 pseudo-random self-similar sequence 생성기의 비교분석을 위한 좀더 좋은 방법이 필요하다는 것을 보여주었다.

It is generally accepted that self-similar (or fractal) processes may provide better models for teletraffic in modern telecommunication networks than Poisson Processes. If this is not taken into account, it can lead to inaccurate conclusions about performance of telecommunication networks. Thus, an important requirement for conducting simulation studies of telecommunication networks is the ability to generate long synthetic stochastic self-similar sequences. Three generators of pseudo-random self-similar sequences, based on the FFT〔20〕, RMD〔12〕 and SRA methods〔5, 10〕, are compared and analysed in this paper. Properties of these generators were experimentally studied in the sense of their statistical accuracy and times required to produce sequences of a given (long) length. While all three generators show similar levels of accuracy of the output data (in the sense of relative accuracy of the Horst parameter), the RMD- and SRA-based generators appear to be much faster than the generator based on FFT. Our results also show that a robust method for comparative studies of self-similarity in pseudo-random sequences is needed.

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