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Masking the prestige of instant networks and their destiny power because the prepares for 4G, this paintings adopts a logical strategy, starting every one bankruptcy with introductory fabric, sooner than continuing to extra complex themes and instruments for approach analysis.
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J. (1999) Renormalization group analysis of the small-world network model. Physics Letters A, 263 (4), 341–346. S. and Rao, R. (2011) A realistic small-world model for wireless mesh networks. IEEE Communications Letters, 15 (4), 455–457. , and Loureiro, A. (2008) On the Design of Heterogeneous Sensor Networks Based on Small World Concepts. 11th International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM 08), 2008, Vancouver, Canada, p. 309314.  Brust, M.
In terms of network topology, clustering means the presence of a heightened number of triangles in the network (sets of three vertices each of which is connected to each other’s) . Based on this, in our model, we can quantify the clustering coefficient C as C= i w i w p p p j iw wj ji p p j iw wj ,i w j 179 where the numerator indicates the average number of triangles in the network and the denominator, the average number of connected triples of vertices defined as a single vertex with edges running to an unordered pair of others.
16 Chapter 16: Network Optimization Theory There is a varity of network optimization tools that enable best network parameters selection in accordance with some objective function, often referred to as utility function. In this chapter we provide a brief overview of these tools. More specifically we cover topics as: layering as optimization decomposition, cross-layer optimization, and optimization problem decomposition methods. 17 Chapter 17: Network Information Theory Network optimization theory provides tools to analyze maximum achievable rates (capacity) in the network.