Lecture 15 - Presentations by Engin and Esra

This lecture started by Engin's presentation about Network Interaction and animation. He first explained the geo-localization term which is mapping network objects with respect to their physical location. Geo-localization is important in terms of providing many new location aware services, and it helps to manage and diagnose network. After explaining the geo-localization term and its properties he focused on explaining the main goal of his project. The main goal of his project is building a network interaction and animation tool which will obtain location of routers and visualize them. This will be able to display properties of the network objects and generate random traffic flow. It will allow user to change network parameters and observe how these parameters effect the network performance. He talked about related works and missing parts in the related works (Dimes, Internet 2, NAm). In conclusion this work will be a game of network structure which will allow user to play with the parameters of the network to see the performance of the network. This project can also be used for training in different companies, ISPs and educational institutions.

Next, Esra presented her project about Gene Expression Networks. She explained the term of stress which is the factor that affects the plant grow in the natural environment.Every organism gives different responses to different stresses they are subjected to and they have to improve themselves by adapting changes in environment and to other stress conditions. In general we can say that the plants are affected adversely by these conditions and thus as a result human life will also be affected by the stresses that plants encounters. The main goal of this project is to analyze the stress tolerance of crops; rice, wheat and maize under drought, high salinity and low temperature and study the sets of genes that give any response to these stresses separately. For every stress condition there will be an undirected graph whose vertices correspond to genes, and the vertices of two genes are connected by an edge if their expressions are correlated. Once this network is constructed she will apply the metrics of complex network theory to analyze the network.