The grant money will be used to turn the Master of Science in Computer Networks to a Professional Science Master (PSM).

Network monitoring and measurement can be regarded as an essential function for developing education, research and corporate networks that can support innovative networking technologies, such as video-based distance learning applications and cloud computing infrastructures. We propose to design and implement a passive network monitoring tool that will be able to characterize novel applications, provide early warning for security incidents and provide traffic measurements available to the community through a web-based NCSU/NCREN network map. Following the measurement phase we propose to develop a traffic modeling mechanism that will identify the structural dependencies of traffic as it relates to social connectivity graphs and distances. More specifically our focus will be on: (1) conducting a series of detailed trials to capture data from different places across research and education campuses and identify the emerging traffic patterns; (2) using the trial results to deconstruct and analyze the intersecting networking and social distances of next generation of users (K-20); (3) incorporating these traffic patterns into a queueing model of a flow of IP packets with a view to calculating the end-to-end delay and packet loss rate. The results from this model will be used in cost-based parametric model in order to obtain the optimal network topology architecture.

The award will fund research activities aiming to make significant contributions to the capacity planning and automation for monitoring tools by use of modeling, simulation, testbed emulation and on line optimization. Specific goals include the study of models, response surfaces and advanced simulation methods, and, the creation of an automated paradigm for on-line optimization for capacity tuning.