Most of these networks are genetic, worldwide web-based with a complex topology. A scale-free network is a connected network with the property that the number of links originating from a given mode exhibits a powerful law of distribution. This is network is constructed by adding nodes to the existing network progressively and also introducing new links to the already existing nodes with preferential attachment. This network expands continuously by the addition of new vertices (links) and these new links are attached to sites that are already well connected. Mathematically, the probability of linking the new node to the proportion to the existing links is what brought about the existence of the two networks. Examples of scale-free networks in science and engineering disciplines are the topology of web pages, where nodes are used on individual pages and links represent hyperlinks. Nodes and links function together simultaneously. Where the nodes are transformers, substations and generators, links are power transmitter lines. This description of scale-free networks indicates that the development of large networks is controlled by robust-self organizing phenomena that go beyond the already evaluated individual systems (Albert-Laszlo, 2003).
Random networks are models that assume the probabilities of two vertices connected are random and uniform which is not the case. Most real networks exhibit preferential connectivity. For example, the newly created webpage includes links to popular websites with already high connectivity. This example indicates there is a high probability that the vertex will be linked to an already existing large number of connections. Examples of these networks include business networks, transportation networks and social networks entailing individuals and organizations. Networks are classified in single clusters denoted by nodes and they connect to each other by moving along the links between the nodes. The networks are characterized by large fractions of all nodes, a term is known as percolation. When nodes are randomly picked and connected together in a network, it changes. When clusters are joined, people everywhere are connected together Random network theory therefore explains that the average number of links per node increases beyond the critical one and the number of links out in the giant cluster decreases simultaneously. What does this mean? It means that no nodes are left isolated, they all are included in the network connection (Albert-Laszlo, 2003, p.18).
The degree of distribution in random networks follows a bell curve. This description tells us that most nodes have the same number of links and nodes that have very larger number of links are non-existence. Illustrated example of random network is a national highway network. The nodes represent the cities and the links represent major highways. Normally, most cities are served by the same number of highways. Contrary, the power-law degree of distribution denoted that most nodes have few links and are held together by highly connected hubs (Albert-Laszlo, 2003, p.71).
The difference between random networks and scale-free networks is that they are both classified as “small world” networks. This means that it takes little time to get from one node to another and the science underlying the phenomena is that there are only six degrees of separation between two people in the world. Therefore both the networks with or without connected nodes do not take them long to connect with another node. Example of scale-free networks is that of Yahoo Inc since many transactions are funneled through well-connected hub nodes. The other difference occurs where the network breaks down. Randomly distributed networks for instance steadily decays as nodes fail to break into smaller domains that are unable to communicate. While scale-free networks may not show degradation as random nodes fail. They maintain connectivity of the networks throughout which does not stop working (Albert-Laszlo, 2003, p.40).
A network is an interconnection of systems. Alberto-Lazlo Barabasi describes different networks entailing social, graph theories and six degrees in trying to define the connectivity between the nodes and links. Graph theory is an example of a network and does not qualify as a system because it only requires one acquaintance to form a society. It does not also provide a link between social networks or random graphs and focuses exclusively on regular graphs which do not have ambiguity about their structure. These graphs when first transformed from social networks to phones lines, were not regular. This complexity classifies these networks as random (Albert-Laszlo, 2003, p.19).
Real networks must have organized principles. Second, we have social network which links people of different classes together. In an organized party, you will find hundreds of perfect strangers trying to connect with each other in the room and later organize themselves in groups. These are inevitable social links created between people who met earlier but have formed different groups. As a consequence, these strangers may start connecting people who are still strangers to each other. For example, at a conference I was invited to, I met Joseph who is a perfect stranger to me. Numerous conversations link as together then I move to another group where I meet Mary. Later, I will make sure I introduce Joseph to Mary, and so on. As the list goes on, guests will be interwoven by these intangible links creating a web of acquaintances. This qualifies as a system since it interlinks people of different networks together (Albert-Laszlo, 2003, 15).
Six degrees is another network that links people of the whole world together. It explains that everyone on the planet is separated by only six other people. How is this person connected? These people are connected through reading sociology papers, watching movies and many more. For instance, when watching a true-life story movie, we laugh, cry or even emulate characters. By this, we try to put ourselves the life of the character displayed as prevailed in our popular thoughts. This connects us to that particular person whoever he is residing from. Six degrees theory qualifies as system since it uses communication media to connect people from various locations (Albert-Laszlo, 2003, p.29).
Internet is similar to the traditional human system in the sense that in the sense that it’s a worldwide social net. It provides a path between any two people in this internet connectivity. There is always a connection path between two items in the universe; two neurons in our brain interconnect with each other, two companies interconnect and just about anything. Nothing in the world is excluded interconnected web of life. It’s also similar to human systems because the nodes are integrated into a single complex cellular map whose links easily affect millions and within which all node is controlled. Internet connections are important components in human social networks. It makes important deals, brings people of different races and educational levels together and helps launch new businesses. The implication of a design system for the full cycle is that they create threads of society, linking people worldwide. Cyberspace (internet connection) embodies freedom of speech. It makes the web a forum for democracy in which everyone’s voice is heard without biasness. Internet as a network was designed to be distributed to efficiently create communication networks. All nodes and links correlate to provide connectivity. Some nodes have huge number of links while others only contain a few. Once web pages are published, they instantly become available to everyone around the world with an internet connection. What has become challenging is that millions of documents become posted on the internet everyone and they might not be noticed unless it’s visible to all readers (Albert-Laszlo, 2003, p. 57).
References
Albert-Laszlo, B. (2003). Linked: The New Science of Networks. Perseus Pub.