NDLI: Loss ratio simulation method of MMPP/D/1/K using statistical techniques

Content Provider	IEEE Xplore Digital Library
Author	Toyoshima, K.
Copyright Year	2012
Description	Author affiliation: NTT Network Innovation Laboratories, 1-1 Hikari-no-oka Yokosuka, Kanagawa, Japan (Toyoshima, K.)
Abstract	For network planning and the operation of video streaming multicast services, it is very important to grasp the characteristics of packet loss against traffic type and buffer size because multicast uses UDP, not TCP, so packet recovery is not assured in this layer. This is possible by using Monte Carlo simulations (MCS), one of the most effective techniques. Although approximate methods have also been proposed as alternatives, in most cases, MCS results are provided to validate the proposal. However, there is no obvious way of determining when MCS should be terminated. This paper proposes a new obvious termination method for embedding in the MMPP/D/1/K MCS program that focuses on loss interval; it employs statistical techniques that allow loss ratios to be accurately estimated in the shortest possible time. The simulation is terminated when the $χ^{2}-statistic$ becomes less than or equal to a critical value, and the loss ratio is calculated from the number of all losses up to that time. A method of determining the parameters needed to calculate the $χ^{2}-statistic$ is also proposed to reduce the calculation time in MCS. To evaluate the proposed method, confidence intervals are obtained by applying the proposed method to six cases. Long-term loss ratios for the six cases are within 95 percent confidence intervals. 95 percent confidence intervals for the six cases are near approximate loss ratios. Embedding the proposed method in the MCS program imposes a time penalty of only 3.6 percent at most. The proposed method is thus very useful and usable.
Starting Page	1
Ending Page	6
File Size	276297
Page Count	6
File Format	PDF
ISBN	9781467327107
e-ISBN	9789532900361
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-11
Publisher Place	Croatia
Access Restriction	Subscribed
Rights Holder	University of Split
Subject Keyword	Exponential distribution Sociology Streaming media Approximation methods Statistics
Content Type	Text
Resource Type	Article

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