By Dieter Claeys, Joris Walraevens, Koenraad Laevens, Bart Steyaert, Herwig Bruneel (auth.), Khalid Al-Begain, Dieter Fiems, William J. Knottenbelt (eds.)
This ebook constitutes the refereed court cases of the seventeenth foreign convention on Analytical and Stochastic Modeling recommendations and functions, ASMTA 2010, held in Cardiff, united kingdom, in June 2010. The 28 revised complete papers awarded have been rigorously reviewed and chosen from quite a few submissions for inclusion within the e-book. The papers are prepared in topical sections on queueing idea, specification languages and instruments, telecommunication structures, estimation, prediction, and stochastic modelling.
Read or Download Analytical and Stochastic Modeling Techniques and Applications: 17th International Conference, ASMTA 2010, Cardiff, UK, June 14-16, 2010. Proceedings PDF
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Additional info for Analytical and Stochastic Modeling Techniques and Applications: 17th International Conference, ASMTA 2010, Cardiff, UK, June 14-16, 2010. Proceedings
It is summarized in Table 1. The centralized management. The protocol realized in this paper is utilizing a centralized management which introduces extra wiring costs to the system since it utilizes N 2 detached links for information exchange. Considering the fact that only a centralized controller is performing the information exchange, we get 2N vectors of N bits as a total communication overhead in the system. Moreover, due to a simple bit-by-bit comparison (logical OR) performed in decision matrix of the controller the computation overhead is negligible and is constant in time.
The phase lasts until the queue becomes empty and no more customers are present in the system. The phase 2 duration is the result of two aspects: the number of customers in the queue at the start of the phase and the number of new customer arrivals during the phase. Therefore we ﬁrst introduce Δ as the time that is needed to reduce the number of customers in the system by 1. The total number of customers in the system only decreases when no new customers arrive, whereas it remains unaltered when there is an arrival.
Let us introduce the matrix G as solution to equation Q+ G 2 + Q0 G + Q− = O. The matrix G is computed by means of method of iterations from the recurrent relations G(n + 1) = (−Q0 )−1 Q+ G 2 (n) + (−Q0 )−1 Q− starting from G(0) = O and iterating until the matrix G(m) becomes be stochastic for some m. Eﬀective implementation of this recurrent procedure is presented in . When computation of the matrix G is completed, the matrix R is computed by R = Q+ (−Q0 − Q+ G)−1 . 6 Performance Measures Having the stationary distribution π i , i ≥ 0, calculated we can ﬁnd a number of stationary performance measures of the system.
Analytical and Stochastic Modeling Techniques and Applications: 17th International Conference, ASMTA 2010, Cardiff, UK, June 14-16, 2010. Proceedings by Dieter Claeys, Joris Walraevens, Koenraad Laevens, Bart Steyaert, Herwig Bruneel (auth.), Khalid Al-Begain, Dieter Fiems, William J. Knottenbelt (eds.)