NeTS-NBD: Characterizing Large-Scale, Dynamic Peer-to-Peer Networks: New Sampling and Modeling Approaches

University Of Oregon Eugene, Eugene OR

Investigators

Abstract

Despite the importance of the peer-to-peer (P2P) communication paradigm and the far reaching impact of P2P applications on the Internet, fundamental properties concerning the dynamics of large scale P2P applications are not well understood. The fundamental challenge in deriving these characteristics is to capture a representative (i.e. unbiased) view of large scale P2P systems as they evolve over time. This project investigates and develops new measurement and modeling methodologies to understand and accurately characterize properties of the dynamics of large scale P2P systems. For example, the PIs identify the topological and temporal sources of bias in estimating peer connectivity and peer properties. The PIs also examine the idea of sampling dynamic graphs as a novel approach to capture representative measurements in large and dynamic P2P systems. An innovative combination of empirical and modeling efforts (along with simulation) is leveraged to accurately derive key characteristics of P2P systems, identify their underlying causes, and study their implications for the design and evaluations of future P2P systems. Broader Impact: The resources contributed by this project have far-reaching implications on the research and development of P2P systems and include (i) a set of new high-fidelity measurement methodologies and tools, (ii) a novel class of evolutionary models that account for the dynamic properties of existing P2P systems, (iii) a publicly available archive of measurements of actual P2P systems, and (iv) a new modular session-level P2P simulator. The resulting measurement methodologies, models and tools will be incorporated into newly developed courses at the undergraduate and graduate levels at the University of Oregon.