Network theory in the context of "Routable"

A heterarchy is a system of organization where the elements of the organization are unranked (non-hierarchical) or where they possess the potential to be ranked a number of different ways. Definitions of the term vary among the disciplines: in social and information sciences, heterarchies are networks of elements in which each element shares the same "horizontal" position of power and authority, each playing a theoretically equal role. In biological taxonomy, however, the requisite features of heterarchy involve, for example, a species sharing, with a species in a different family, a common ancestor which it does not share with members of its own family. This is theoretically possible under principles of "horizontal gene transfer".

A heterarchy may be orthogonal to a hierarchy, subsumed to a hierarchy, or it may contain hierarchies; the two kinds of structure are not mutually exclusive. In fact, each level in a hierarchical system is composed of a potentially heterarchical group.

A street network is a system of interconnecting lines and points (called edges and nodes in network science) that represent a system of streets or roads for a given area. A street network provides the foundation for network analysis; for example, finding the best route or creating service areas.

They greatly affect in-town movement and traffic. Street networks can become very complex in cities. Street networks are very often localized, because there is little non-highway transportation from town to town. The U.S. Highway System is like a street network, but it is national, and consists of highways instead of streets and roads.

In the context of network theory, a complex network is a graph (network) with non-trivial topological features—features that do not occur in simple networks such as lattices or random graphs but often occur in networks representing real systems. The study of complex networks is a young and active area of scientific research (since 2000) inspired largely by empirical findings of real-world networks such as computer networks, biological networks, technological networks, brain networks, climate networks and social networks.

Dynamic network analysis (DNA) is an emergent scientific field that brings together traditional social network analysis (SNA), link analysis (LA), social simulation and multi-agent systems (MAS) within network science and network theory. Dynamic networks are a function of time (modeled as a subset of the real numbers) to a set of graphs; for each time point there is a graph. This is akin to the definition of dynamical systems, in which the function is from time to an ambient space, where instead of ambient space time is translated to relationships between pairs of vertices.

Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. Examples of social structures commonly visualized through social network analysis include social media networks, meme proliferation, information circulation, friendship and acquaintance networks, business networks, knowledge networks, difficult working relationships, collaboration graphs, kinship, disease transmission, and sexual relationships. These networks are often visualized through sociograms in which nodes are represented as points and ties are represented as lines. These visualizations provide a means of qualitatively assessing networks by varying the visual representation of their nodes and edges to reflect attributes of interest.

Social network analysis has emerged as a key technique in modern sociology. It has also gained significant popularity in the following: anthropology, biology, demography, communication studies, economics, geography, history, information science, organizational studies, physics, political science, public health, social psychology, development studies, sociolinguistics, and computer science, education and distance education research, and is now commonly available as a consumer tool (see the list of SNA software).

Routing is the process of selecting a path for traffic in a network or between or across multiple networks. Broadly, routing is performed in many types of networks, including circuit-switched networks, such as the public switched telephone network (PSTN), and computer networks, such as the Internet.

In packet switching networks, routing is the higher-level decision-making that directs network packets from their source toward their destination through intermediate network nodes by specific packet forwarding mechanisms. Packet forwarding is the transit of network packets from one network interface to another. Intermediate nodes are typically network hardware devices such as routers, gateways, firewalls, or switches. General-purpose computers also forward packets and perform routing, although they have no specially optimized hardware for the task.

Core–periphery structure is a network theory model.