By Christina Aperjis, Michael J. Freedman, Ramesh Johari (auth.), Eitan Altman, Augustin Chaintreau (eds.)

This e-book constitutes the refereed lawsuits of the second one Euro-NF overseas convention, NET-COOP 2008 held in Paris, France, in September 2008.

The thirteen revised complete papers provided have been rigorously reviewed and chosen from a complete of 27 submissions. The papers are geared up in topical sections on economics and peer-to-peer networks; routing and measurements; scheduling; tcp and congestion regulate; in addition to instant networks.

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Extra info for Network Control and Optimization: Second Euro-NF Workshop, NET-COOP 2008 Paris, France, September 8-10, 2008. Revised Selected Papers

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Uk Abstract. We propose a stochastic model for a file-sharing peer-to-peer network which resembles the popular BitTorrent system: large files are split into chunks and a peer can download or swap from another peer only one chunk at a time. We exhibit the fluid and diffusion limits of a scaled Markov model of this system and look at possible uses of them to draw practical conclusions. 1 Introduction Peer-to-peer (p2p) activity continues to represent a very significant fraction of overall Internet traffic, 44% by one recent account [4].

16(8), 873–888 (2000) 5. : A short convergence proof for a class of ant colony optimization algorithms. IEEE-EC 6, 358–365 (2002) 6. : Modeling the dynamics of ant colony optimization. Evolutionary Computation 10(3), 235–262 (2002) 7. : Search bias in ant colony optimization: on the role of competition-balanced systems. IEEE Trans. Evolutionary Computation 9(2), 159– 174 (2005) 8. : Ant colony optimization and stochastic gradient descent. Artificial Life 8(2), 103–121 (2002) 9. : AntHocNet: An ant-based hybrid routing algorithm for mobile ad hoc networks.

As a result, the probability Pk (t), of agents choosing path k at time t + 1 is greater than the probabilities on the other paths. It is shown in [1] that initial bias builds up towards the shortest path k, that in turn drives the algorithm to converge to it. 3 Multi-stage Shortest Path Problem Consider the graph representation of a generic multi-stage shortest path problem with K stages. Each stage k is denoted by Sk . Stage S0 contains a single source node S and stage SK+1 has a single destination node D.

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