networking

Examples of networking in the following topics:

• Types of Networks

  • A storage area network (SAN) is a dedicated network that provides access to consolidated, block level data storage.
  • A campus area network (CAN) is a computer network made up of an interconnection of LANs within a limited geographical area.
  • A backbone network is part of a computer network infrastructure that interconnects various pieces of network, providing a path for the exchange of information between different LANs or subnetworks.
  • Network performance management, including network congestion, are critical parameters taken into account when designing a network backbone.
  • Backbone networks are similar to enterprise private networks.

• Routing

  • Routing is the process of selecting paths in a network along which to send network traffic.
  • Routing is the process of selecting paths in a network along which to send network traffic.
  • Routing is performed for many kinds of networks, including the telephone network (circuit switching), electronic data networks (such as the internet), and transportation networks.
  • A transport network, (or transportation network in American English), is typically a network of roads, streets, pipes, aqueducts, power lines, or nearly any structure which permits either vehicular movement or flow of some commodity.
  • A transport network may combine different modes of transport.

• Social Networks

  • Facebook is an example of a large social network.
  • Social networks are composed of nodes and ties.
  • Smaller, tighter networks composed of strong ties behave differently than larger, looser networks of weak ties.
  • The study of social networks is called either social network analysis or social network theory.
  • Assess the role of social networks in the socialization of people

• Modality and levels of analysis

  • The network analyst tends to see individual people nested within networks of face-to-face relations with other persons.
  • Often these networks of interpersonal relations become "social facts" and take on a life of their own.
  • A family, for example, is a network of close relations among a set of people.
  • Most social network analysts think of individual persons as being embedded in networks that are embedded in networks that are embedded in networks.
  • In chapter 17, we'll take a look at some methods for multi-mode networks.

• Network Models of Memory

  • Network models are based on the concept of connectionism.
  • There are several types of network models in memory research.
  • Some define the fundamental network unit as a piece of information.
  • However, network models generally agree that memory is stored in neural networks and is strengthened or weakened based on the connections between neurons.
  • PDP posits that memory is made up of neural networks that interact to store information.

• Summary

  • In this chapter we've taken a look at some of the most basic and common approaches to applying statistical analysis to the attributes of actors embedded in networks, the relations among these actors, and the similarities between multiple relational networks connecting the same actors.
  • But, there is still a good bit more, as the application of statistical modeling to network data is one of the "leading edges" of the field of social (and other) network analyses.
  • First, for very large networks, methods for finding and describing the distributions of network features provide important tools for understanding the likely patterns of behavior of the whole network and the actors embedded in it.
  • Second, we have increasingly come to realize that the relations we see among actors in a network at a point in time are best seen as probabilistic ("stochastic") outcomes of underlying processes of evolution of networks, and probabilistic actions of actors embedded in those networks.
  • And, we've taken a look at a variety of approaches that relate attributes of actors to their positions in networks.

• Network Structure

  • In the network structure, managers coordinate and control relationships with the firm that are both internal and external.
  • The concept underlying the network structure is the social network—a social structure of interactions.
  • At the industry level, complex networks can include technological and innovation networks that may span several geographic areas and organizations.
  • A network organization sounds complex, but it is at its core a simple concept.
  • Like other organizational structures, the network structure has its advantages and its disadvantages.

• Introduction

  • The basic idea of a social network is very simple.
  • Networks can have few or many actors, and one or more kinds of relations between pairs of actors.
  • The amount of information that we need to describe even small social networks can be quite great.
  • All of the tasks of social network methods are made easier by using tools from mathematics.
  • For the manipulation of network data, and the calculation of indexes describing networks, it is most useful to record information as matrices.

• Networks

  • The study of social networks is called both social network analysis and social network theory.
  • Social network theory views social relationships in terms of nodes and ties.
  • The shape of the social network helps determine a network's usefulness to its individuals.
  • Smaller, tighter networks can be less useful to their members than networks with lots of loose connections (weak ties) to individuals outside the main network.
  • It is better for individual success to have connections to a variety of networks rather than many connections within a single network.

• Preface

  • This book began as a set of reading notes as Hanneman sought to teach himself the basics of social network analysis.
  • It then became a set of lecture notes for students in his undergraduate course in social network analysis.
  • Our goal in preparing this book is to provide a very basic introduction to the core ideas of social network analysis, and how these ideas are implemented in the methodologies that many social network analysts use.
  • Social network analysis is a continuously and rapidly evolving field, and is one branch of the broader study of networks and complex systems.
  • The concepts and techniques of social network analysis are informed by, and inform the evolution of these broader fields.