Tracing Structures in Networks to Capture its Organization

Tracing Structures in Networks to Capture its Organization

Karina Raya-Díaz (Autonomous University of Baja California, Tijuana, Mexico), Carelia Gaxiola-Pacheco (Autonomous University of Baja California, Tijuana, Mexico) and Manuel Castañón-Puga (Autonomous University of Baja California, Tijuana, Mexico)
Copyright: © 2015 |Pages: 13
DOI: 10.4018/IJAEC.2015100101
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Abstract

This article analyzes the central nervous system as a dynamic complex system, focusing on the micro-interactions that allow neurons to become part of a network. The purpose of this analysis is to identify organizational levels generated in neural networks when a fault occurs and how topological structures are created during the information transmission, as in computer networks. The calculation of clustering coefficient was using as a method to observe the association of each node of the network. A dendrogram was created to reflect the changes in the interactions of the links of nodes.
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Computer Network Structures

Computer networks are complex systems because they are dynamic, have autonomous behavior, there is no central control node, and have nonlinear interactions (Mitchell & Mitchell, 2006), (Raya-Díaz, Gaxiola-Pacheco, & Castañón-Puga, 2014). The Figure 1 shows a network example of six nodes interconnected by links, each node has neighbors that help transmit package information from one node to another. The number of links coming into or out of a node is known as the degree. The nodes that have a high degree, like node B, are called hub node; in real networks, if this kind of node goes down (off), a congestion behavior could emerge as some of its neighbors become unable to establish communication if there is no other path that can be used to do it (e. g. nodes A and E).

Figure 1.

Network topology

Path Length

Two important aspects of a computer network are the path length, which can be calculated by the number of hops needed to reach one node from another, and the sequence, which describes the path. Due the dynamics of a real computer network the paths may change through time; the path lengths with the number of hops to reach every node of the network, assuming the shortest path, are shown in the Table 1. If a node is added to the network, emerges a new behavior, and the path lengths of each node affected are updated according to the new topology and the emerging behavior.

Table 1.
Path lengths for each node
NodesABCDEF
A011223
B101112
C110122
D211021
E212203
F322130

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