The main focus of this IPAM program will be on innovations and breakthroughs in the theoretical foundations and practical implementations of a network-centric multi-resolution analysis (MRA); that is, a structured approach to representing, analyzing, and visualizing complex measurements from Internet-like systems that is (i) specifically designed to accommodate the vertical (e.g., layers) and horizontal (e.g., domains) decompositions of Internet-like architectural designs, (ii) flexible enough to account for the highly heterogeneous (i.e., “scale-rich”) nature of these designs and the high semantic content of the available measurements, and (iii) capable of retaining some of the mathematical elegance of more traditional MRA schemes. Critical capabilities of the envisioned Internet MRA, in particular, and network MRA, in general, include support for the exploration of multi-scale representations of very large and diverse network-specific annotated graph structures, novel techniques for the study of the dynamics of as well as the dynamic processes over these structures, and new methodologies and tools for dealing with aggregated spatio-temporal-functional network data representations and their associated analysis and visualization.
By leading the way towards the development of a mathematical foundation for network-centric MRA techniques, this IPAM program will be firmly grounded in a number of key Internet MRA target problems (e.g., cyber-security, traffic/network engineering, network control), with close ties to activities that can be expected to arise in the context of a major NSF-led initiative called Global Environment for Networking Innovations or GENI (www.cise.nsf.gov/geni or www.geni.net). At the same time, this IPAM program will also be strongly influenced by developments in other scientific disciplines where informed multiscale approaches to the study of highly engineered or evolved networked systems have proved to be essential for advancing our understanding of their properties, behaviors, and evolution.
(University of Wisconsin-Madison)
John Doyle (California Institute of Technology)
Anna Gilbert (University of Michigan)
Mauro Maggioni (Duke University)
Craig Partridge (BBN Technologies)
David Rincon (Universitat Politécnica de Catalunya)
Matthew Roughan (University of Adelaide)
Walter Willinger (AT&T Technologies, Engineering Research Center)