Abstract
In this chapter, we present a new method to analyze the performance of Automatic Repeat reQuest (ARQ) schemes in self-similar traffic. Taking into account the self-similar nature of a massive-scale wireless multimedia service, we build a batch arrival queueing model and suppose the batch size to be a random variable following a Pareto(c,α) distribution. Considering the delay in the setting up procedure of a data link, we introduce a setup strategy in this queueing model. Thus a batch arrival Geom X/G/1 queueing system with setup is built in this chapter. By using a discrete-time embedded Markov chain, we analyze the stationary distribution of the queueing system and derive the Probability Generation Functions (P.GFs.) of the queueing length and the waiting time of the system. We give the formula for performance measures in terms of the response time of data frames, setup ratios, and offered loads for different ARQ schemes. Numerical results are given to evaluate the performance of the system and to show the influence of the self-similar degree and the delay of the setup procedure on the system performance.
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Acknowledgments
This work was supported in part by MEXT.ORC (2004–2008) and GRANT-IN-AID FOR SCIENCE RESEARCH (No. 19500070), Japan and was supported in part by NSF (No. 10671170) and NSF (No. 60773100), China.
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Jin, S., Yue, W., Tian, N. (2009). Performance Analysis of ARQ Schemes in Self-Similar Traffic. In: Yue, W., Takahashi, Y., Takagi, H. (eds) Advances in Queueing Theory and Network Applications. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09703-9_13
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DOI: https://doi.org/10.1007/978-0-387-09703-9_13
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