NETWORKING 2011 Workshops: International IFIP TC 6 by Attahiru S. Alfa, Vicent Pla, Jorge Martinez-Bauset, Vicente

By Attahiru S. Alfa, Vicent Pla, Jorge Martinez-Bauset, Vicente Casares-Giner (auth.), Vicente Casares-Giner, Pietro Manzoni, Ana Pont (eds.)

This booklet constitutes the refereed post-conference lawsuits of 4 workshops colocated with NETWORKING 2011, held in Valencia, Spain, in may possibly 2011: the Workshop on functionality evaluate of Cognitive Radio Networks: From idea to truth, PE-CRN 2011, the community Coding purposes and Protocols Workshop, NC-Pro 2011, the Workshop on instant Cooperative community defense, WCNS 2011, and the Workshop on Sustainable Networking, sundown 2011. The 28 revised complete papers offered have been rigorously reviewed and chosen from a number of submissions. The papers hide a variety of themes addressing the most examine efforts within the fields of community coding, sustainable networking, defense in instant cooperative networks, and function evaluate of cognitive radio networks.

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Additional info for NETWORKING 2011 Workshops: International IFIP TC 6 Workshops, PE-CRN, NC-Pro, WCNS, and SUNSET 2011, Held at NETWORKING 2011, Valencia, Spain, May 13, 2011, Revised Selected Papers

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We define {Xt,St,Ŝt} to be the process of the entire system for which at time t there are Xt (Xt∈{0,1,2,…}) queued packets of the SU. This process forms a three dimensional CTMC illustrated in Fig. 2, which is homogeneous, irreducible and stationary. The exact structure of transitions within the CTMC is constructed in the same manner as in [9],[13]. Next, matrix-geometric approach is applied to calculate the steady state probabilities of CTMC. Then, the average number of queued packets of SU can be calculated and by using the Little's law one can obtain the waiting time W of the SU.

In: Proc. IEEE Int. Conf. Commun(ICC), pp. : Optimization of spectrum sensing for opportunistic spectrum access in cognitive radio networks. In: Proc. 4th IEEE CCNC, pp. : Cross-Entropy Optimized Cognitive Radio Policies. : The Cross Entropy Method. A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning. ser. Information Science and Statistics. : The cross-entropy method for fast policy search. In: Proceedings of 20th International Conference on Machine Learning (ICML 2003), Washington, US, pp.

0, . . , jV + q) (i + 1, jW , . . , jk , . . , jV ) kjk μS ... kjk μS λP jk = 0, ∀k < V ; i > 0. jk = 1, k < V ; jm = 0, ∀m < V and m = k . Or jk > 0, k = V ; jm = 0, ∀m < V . −1 q= V m=W jm − 1; k ≥ m)jm − (V − k); V > 1. V −1 m=W (V − b(x) < M . kj k λP b(x) = M ; jk > 0, k > W ; V > 1. PU arrives. An SU service (i + 1, jW , . . , M −i with k channels reduces its jk−1 + 1, jk − 1, aggregated channels . . , jV ) W jW PU arrives and an SU ser- (i + 1, jW − 1, λP jW = 1; jk = 0, W + 1 ≤ k ≤ V − 1; M −i vice is terminated.

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