By Satoshi Tanaka, Kyoko Hasegawa, Rui Xu, Naohisa Sakamoto, Stephen John Turner
This ebook constitutes the refereed complaints of the 14th overseas convention on structures Simulation, Asia Simulation 2014, held in Kitakyushu, Japan, in October 2014. The 32 revised complete papers awarded have been rigorously reviewed and chosen from sixty nine submissions. The papers are equipped in topical sections on modeling and simulation expertise; community simulation; excessive functionality computing and cloud simulation; numerical simulation and visualization; simulation of instrumentation and keep an eye on program; simulation know-how in different greater schooling; basic function simulation.
Read Online or Download AsiaSim 2014: 14th International Conference on Systems Simulation, Kitakyushu, Japan, October 26-30, 2014. Proceedings PDF
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Extra info for AsiaSim 2014: 14th International Conference on Systems Simulation, Kitakyushu, Japan, October 26-30, 2014. Proceedings
C Springer-Verlag Berlin Heidelberg 2014 Server Distribution Policies in Peer-Assisted File Distribution 49 through the ﬁxed and mobile network, request to download the same ﬁle in the shortest possible time. Hence, the performance of content distribution is often aﬀected by a phenomenon called ﬂash crowd, where there is a sudden large surge in the number of users, which usually occurs when new content is made available . As content ages, the ﬂash crowd subsides and the system goes into steady-state, when the arrival rate of the users becomes closer to the service rate of the system.
4. 5 -1 0 20 40 60 Time[points] 80 100 Fig. 5. The estimated impulse response using the proposed method (input SNR is 10dB) First, we show a result of the simulation using the sparse impulse response of which the input SNR between s(t) and e(t) is 10dB. 4 shows the estimated impulse response using the method based on the mean square error. 5 illustrates the estimated impulse response using the proposed method. 4 and 5, each of the impulse responses is similar to the original response. 32 K. Kito and T.
32 K. Kito and T. Murakami 45 proposed Output SNR[dB] 40 mean square error 35 30 25 20 5 10 Input SNR[dB] 15 20 Fig. 6. 1 0 20 40 60 Time[points] 80 100 Fig. 7. 6 shows the performance comparison in terms of SNRs. 6, the output SNRs are improved about 4dB by the proposed method in contrast to the method based on the mean square error. Second, we show a result of the simulation using the impulse response as a sinc function of which the input SNR between s(t) and e(t) is 10dB. 7 depicts the estimated impulse response using the method based on the mean square error.
AsiaSim 2014: 14th International Conference on Systems Simulation, Kitakyushu, Japan, October 26-30, 2014. Proceedings by Satoshi Tanaka, Kyoko Hasegawa, Rui Xu, Naohisa Sakamoto, Stephen John Turner