During the past decade, the Internet has witnessed a dramatic increase in the popularity of Peer-to-Peer (P2P) applications. This has caused a significant growth in the volume of P2P traffic. This trend has been particularly alarming for the Internet Service Providers (ISPs) that need to cope with the associated cost but have limited control in routing or managing P2P traffic. To alleviate this problem, researchers have proposed mechanisms to reduce the volume of external P2P traffic for individual ISPs. However, prior studies have not examined the global effect of P2P applications on the entire network, namely the traffic that a P2P application imposes on individual underlying Autonomous Systems (ASs). Such a global view is particularly important because of the large number of geographically scattered peers in P2P applications.

This dissertation examines the global effect of P2P applications on the underlying AS-level Internet. Toward this end, first we leverage a large number of complete overlay snapshots from a large-scale P2P application, namely Gnutella, to characterize the connectivity and evolution of its overlay structure. We also conduct a case study on the performance of BitTorrent and its correlation with peer- and group- level properties. Second, we present and evaluate Respondent-driven sampling as a promising technique to collect unbiased samples for characterizing peer properties in large-scale P2P overlays without requiring the overlay's complete snapshot. Third, we propose a new technique leveraging the geographical location of peers in an AS to determine its geographical footprint and identify the cities where its Points-of-Presence (PoPs) are likely to be located. Fourth, we present a new methodology to characterize the effect of a given P2P overlay on the underlying ASs. Our approach relies on the large scale simulation of BGP routing over the AS-level snapshots of the Internet to identify the imposed load on each transit AS. Using our methodology, we characterize the impact of Gnutella overlay on the AS-level underlay over a 4-year period. Our investigation provides valuable insights on the global impact of large scale P2P overlay on individual ASs.