Techniques

Analytical and Stochastic Modeling Techniques and by Ulf Jensen, Armin Heindl (auth.), Khalid Al-Begain, Dieter

By Ulf Jensen, Armin Heindl (auth.), Khalid Al-Begain, Dieter Fiems, Gábor Horváth (eds.)

This ebook constitutes the refereed lawsuits of the sixteenth overseas convention on Analytical and Stochastic Modeling thoughts and functions, ASMTA 2009, held in Madrid, Spain, in June 2009 together with ECMS 2009, the 23nd ecu convention on Modeling and Simulation.

The 27 revised complete papers offered 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 platforms & distributions; queueing & scheduling in telecommunication networks; version checking & approach 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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Second, we observe that the path ants tend to pick at each time through their heuristic pheromone-basis ACO paradigm is actually the most optimized upstream path in terms of a hybrid metric of both delay and loss ratio. References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. : Multihoming Performance Benefits: An Experimental Evaluation of Practical Enterprise Strategies. In: Proc. : On the Performance Benefits of Multihoming Route Control. : A Measurement-Based Analysis of Multihoming.

In [11], when a PU appears, an SU performs a handoff to the backup channels. If there is no backup channel, the SU is dropped. Figure 2 shows the transition diagram for this access scheme. The number of primary channels, c1 is shared between PUs and SUs. The number of secondary channels, c2 is used as backup channels in case of the sudden appearance of PUs. The process of spectrum access to the primary channels and secondary channels are modeled as a three-dimensional Markov chain. Therefore, states in the transition diagram are described by (i, j, k), where i is the number of primary channels used by PUs, j is the number of primary channels used by the SUs and k is the number of secondary channels used by SUs as backup channels.

Shortest one) which the ants are trying to solve naturally is indeed heuristically solved by this simple approach they follow. Thus far imitating ants’ behavior, diverse numerical problems are solved by employing ACO. See [15] for a complete survey. In this section, after this brief overview on ACO, we formulate the IRC problem as an ACO problem. 1) What are the correspondent elements of IRC in our ant based model? 2) How much pheromone do ants lie down on the path they travel? Is this amount constant or it may change dynamically?

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