Download PDF by Khalid Al-Begain, Dieter Fiems, Gábor Horváth: Analytical and stochastic modeling techniques and
By Khalid Al-Begain, Dieter Fiems, Gábor Horváth
This booklet constitutes the refereed complaints of the sixteenth overseas convention on Analytical and Stochastic Modeling options and purposes, ASMTA 2009, held in Madrid, Spain, in June 2009 along side ECMS 2009, the 23nd eu convention on Modeling and Simulation.
The 27 revised complete papers awarded have been rigorously reviewed and chosen from fifty five submissions. The papers are prepared in topical sections on telecommunication networks; instant & cellular networks; simulation; quueing structures & distributions; queueing & scheduling in telecommunication networks; version checking & technique algebra; functionality & reliability research of assorted systems.
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Comparison of delay of paths at different Fig. 8. Comparison of pheromone of paths time (bottom graph) along with chosen path (top at different time (bottom graph) along with graph) in the commercial IRC in scenario 2 chosen path (top graph) in the ant based IRC in scenario 1 As for TR and TM parameters, the bigger the TM is, the faster ants tend to find the best path. Thus, this actually imposes a trade-off between the amount of overhead we put into the network for probing the destinations through each available path and the speed of convergence which satisfy us.
Choosing a low value for Np, affects the correctness of the measurements and convergence time of the ant based system while a large value for Np imposes too much useless overhead. , before the next switching decision event. If we represent Np on egress link l by Np,l, we have: ∀l TM f N p ,l RTTl (4) where, RTTl denotes the average round trip time on the path correspondent to l . Considering the path with the maximum RTT, we can calculate the upper bound on Np. 2 ms results in an upper bound of 40 for Np.
Al-Begain, D. Fiems, and G. ): ASMTA 2009, LNCS 5513, pp. 42–55, 2009. © Springer-Verlag Berlin Heidelberg 2009 User Access to Popular Data on the Internet ¾ ¾ ¾ ¾ 43 to exploit vacant resources (data, storage, computation power, bandwidth) distributed over user equipment, to adapt to varying demands with scalability for huge communities, including dynamic flash crowds, to embed support for search and replication of data for predefined demands in a self-organizing way, to build and manage overlays without or at low cost for network and server infrastructure.
Analytical and stochastic modeling techniques and applications 16th international conference, ASMTA 2009, Madrid, Spain, June 9-12, 2009: proceedings by Khalid Al-Begain, Dieter Fiems, Gábor Horváth