Download Analytical and stochastic modeling techniques and by Khalid Al-Begain, Dieter Fiems, Gábor Horváth PDF

By Khalid Al-Begain, Dieter Fiems, Gábor Horváth

This booklet constitutes the refereed complaints of the sixteenth foreign convention on Analytical and Stochastic Modeling recommendations and functions, ASMTA 2009, held in Madrid, Spain, in June 2009 along with ECMS 2009, the 23nd ecu convention on Modeling and Simulation.

The 27 revised complete papers awarded have been conscientiously reviewed and chosen from fifty five submissions. The papers are equipped in topical sections on telecommunication networks; instant & cellular networks; simulation; quueing structures & distributions; queueing & scheduling in telecommunication networks; version checking & method algebra; functionality & reliability research of varied systems.

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Additional info for Analytical and stochastic modeling techniques and applications 16th international conference, ASMTA 2009, Madrid, Spain, June 9-12, 2009: proceedings

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The average spectrum usage for the SU is increased by employing licensed channels as operating channels and unlicensed channels as backup channels. The results show a significant improvement of our model compared to the classical OSA in term of blocking and dropping probabilities for SUs. Also, the throughput is increased due to the proposed scheme. In future work, a validation for those metrics will be done through a simulation. References 1. FCC Spectrum Policy Task Force: Report of the spectrum efficiency working group.

Thus, the delay based IRC system has always selected egress link of Path3 (the top graph) in this scenario. On the other hand, Fig. , amount of pheromone on each egress link. As it is seen in this figure, the system works effectively and similar to the commercial delay based system in terms of selecting the best upstream link during every iteration. 8 40 42 44 46 48 50 52 Time (s) Fig. 6. , packets end-to-end delay. Fig. 6 shows the ratio of this end-to-end delay measurement of the ant based system to that of the commercial IRC system for Path1.

Indeed, this is exactly what happens in the ant based IRC and we discuss this more later. Here, we formulate the pheromone evaporation paradigm we use in our ant based IRC. We assume that the initial K0 units of pheromones an ant put 34 H. Hajabdolali Bazzaz and A. Khonsari down on the path are evaporated TE seconds later. This roughly results in a pheroK mone evaporation rate of 0 . ) , recursively by adding up the pheromone value changes during interval T = [t , t + ∆t ] on each path. Specifically, we have: τ s ,i (t + ∆t ) = [τ s,i (t )(1 − ∆t K K0 + )] + ∑ [ K 0 e − age( a ) (1 − (∆age(a )) 0 )] + TE TE a ∈i in T (2) where [ z ]+ = max{0, z} .

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