S. Tarbouriech, C.T. Abdallah, J. Chiasson's Advances in Communication Control Networks PDF

By S. Tarbouriech, C.T. Abdallah, J. Chiasson

ISBN-10: 3540228195

ISBN-13: 9783540228196

The realm of communique and desktop networks has develop into a really lively box of study by means of the keep an eye on structures neighborhood within the final years. instruments from convex optimization and regulate conception are taking part in expanding roles in effective community usage, reasonable source allocation, and verbal exchange hold up lodging and the sector of Networked keep an eye on platforms is speedy changing into a mainstay of keep an eye on platforms study and purposes. This conscientiously edited ebook brings jointly solicited contributions from specialists within the numerous components of communication/control networks concerning either networks below keep watch over (control in networks) in addition to networked keep an eye on platforms (control over networks). the purpose of this publication is to opposite the craze of fragmentation and specialization in verbal exchange keep an eye on Networks connecting a number of interdisciplinary examine fields together with keep watch over, communique, utilized arithmetic and computing device technological know-how.

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9] A. Yan and W. Gong, “Fluid simulation for high-speed networks with flowbased routing,” IEEE Transactions on Information Theory, vol. 45, pp. 1588– 1599, 1999. Control of Communication Networks using IPA on SFM 25 [10] R. Akella and P. Kumar, “Optimal control of production rate in a failure prone manufacturing system,” IEEE Transactions on Automatic Control, vol. 31, pp. 116–126, Feb 1986. [11] J. Perkins and R. Srikant, “The role of queue length information in congestion control and resource pricing,” in Proceedings IEEE Conference on Decision and Control, pp.

Low At s = jω, the set of eigenvalues is identical to that of L( jω) = diag diag µMTr q∗r · e− jωTr jωTr + a · jωTr jωTr + µa ˆ jω) Rˆ T (− jω)R( where ˆ jω) = diag R( 1 cl R( jω)diag x∗r M . (29) Using (29) and (13), the usual argument gives ˆ jω) ≤ 1. ρ Rˆ T (− jω)R( The lemma from [21] then implies that all eigenvalues of L( jω) are in the convex hull: MTr co 0 · Λ( jωTr ) , r = 1, . . , N, (30) q∗r where Λ( jωTr ) := µ · e− jωTr jωTr + a . · jωTr jωTr + µa Note that Λ(·) is independent of r.

For any given a > 0 and µ ∈ (0, 1), the modified Vegas model described by (4) and (22)–(25) is locally asymptotically stable around the equilibrium point (x∗ , y∗ , p∗ , q∗ ) if max xr Tr < r αφ µk0 M φ2 + µ2 (k0 a)2 φ2 + (k0 a)2 (27) or equivalently, if min r q∗r µk0 M > Tr φ where φ = tan−1 φ2 + (k0 a)2 φ2 + µ2(k0 a)2 (28) √ 2 µ 1−µ and α = αr dr is the common target queue length. Proof. The proof proceeds in two steps. First, we follow the argument of [20, 21] to show that the Nyquist trajectories of the loop gain matrix is contained in the convex hull of N complex functions of jω.

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Advances in Communication Control Networks by S. Tarbouriech, C.T. Abdallah, J. Chiasson


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