If you have complex IT solutions everywhere, you’ll never be able to add robustness to your performance. This is why your business services need to sort things out.
As a matter of fact, complex networks exist everywhere, such as the airline network, the power grid network, the interaction network for the road network. All of these networks are robust yet fragile. It means that the networks are robust against some of the random field years but frigid under the malicious attacks. The system by disasters, cascading failures, and intentional attacks on this network deserves an in-depth study.
Robustness in terms of IT Performance
Researchers have proposed many solutions to improve all the robustness in this network. However, apart from many solutions, attention has been paid to the community structure of these networks. The community structure of a network is basically the characteristics of a network that identifies its functionality and should be preserved. With extensive experimentation on the real-world networks, we are here to demonstrate which method is effective and can greatly improve the robustness of the network type, resuming the community structure along with the degree distribution.
There are many complex systems in nature which can be represented as networks. It includes essential infrastructure like airline networks, power grid, protein interaction networks, and so on. As per the research, there are many networks that are robust and seem like an oxymoron. What this really means is that some of the vertices which are called herbs have many more connections as compared to others. The network errors are not limited to the deletion of vertices.
There are four major common measures that can make the network more fragile, i.e. edge deletion, vertex deletion, and edge edition. The addition of edges or what is on the network site makes some important edge vertices more crucial. The deletion of edges is one of the major and common attack measures. The deletion of vertices along with the link address is very harmful. Therefore, focus on the deletion of networks or vertices in order to get rid of all the hassle. These are some of the solutions that typically involve reconfiguration of the network edges.
Besides all the robustness, search reconfiguration will always affect the other key features of these networks, degree distribution and community structure of the networks. Degree distribution is something which clearly captures an amount of information about the network and gives out clues into the structure of a network.
Community structure is a process where functional modules in the network scan provide insight into how network function and topology is affecting each other. When the network is reconfigured it improves your business and you should still retain as much of the original features defining the very nature and functionality of the same. You need to order these drastically and this might cause the network to lose its intended purpose.
For instance, in the US, settlement and population growth is not consistent throughout the whole country and much of the population is concentrated in major cities along the west and east coast. So, power grades are conferred configured such that more power is delivered and distributed throughout the entire country, however, this is not practically possible to configure the power grid network for a better or business.
3 Major Approaches
It can easily ignore the inherent degree of community structure and distribution. so, the major approaches to improve the network robustness can be classified into three main categories –
- The first category is the one that involves the addition of edges to the existing networks. Along with additional edges, it also introduces redundancies which improve the network robust in real life. This is because, with the help of new edges, there come changes in the degree distribution. Moreover, if you add as many edges to network it might dramatically change the community structure of the network.
- The second category of the solution makes network hierarchy instead of adding new edges. All you need to do as reconnect edges in order to make it more effective and robust. It also affects the degree distribution and the community structure of the network.
- Then comes the last category for your business improvement which tries to get rid of the problems of all methods by swapping chosen edges. When you apply the third category method, the original network will convert into an improved network that is an onion-like structure in the form of an improved network with high degree connect vertices and low degree connection with each other. It represents a clear community structure in which we increase the effectiveness as per our choices.
In all other work, we sit to improve the robustness of networks while retaining as much as the defining characteristics as possible. If you really want to effectively quantify robustness, you need to attribute the cost to the changes which can be applied to the to your network. There are three important changes that include –
- The addition of edges
- The change of degree distribution
- The change of community structure
3 step strategy for robustness improvement
In order to improve the robustness of networks, without altering community structure and degree distribution of the networks, there are some of the methods which need to be followed.
- Make every community represent the onion-like structure, swap edges so that the vertices have similar importance when they connect with each other
- Swap the edges in order to make the vertices with high importance connect with vertices with a similar community.
- Properly swap the edges in order to increase the number of edges among the communities.
This can really help out with your business and its services. Community structure is something that plays an important role in various parts such as disease dynamics, cascading failures, and so on. It will provide you with valuable help in understanding the functionality of networks. The change of community structure is also something that leads to the loss of the functional module and the disease network. To prevent the function failure of networks and improving your business, it is really important to solve the issue of your business.
