AI

A unified format for traces of peer-to-peer systems

Abstract

Peer-to-Peer (P2P) systems have recently emerged as a scalable platform for which costs are shared between the system users. Today, P2P technology is serving millions of users world-wide, with applications such as file sharing, video streaming, grid computing, and massively multiplayer online games. Such diversity and scale pose important research and technical problems, which in turn require a much better understanding of the usage patterns and of the performance bottlenecks. However, the large amounts of P2P monitoring and measurement data that already exist have not been made public, for fear of lack of anonymity and in lack of a standard format. To address this problem, in this work we propose a unified format for workloads of P2P systems. Our format stores information coming from many types of P2P applications at several levels of detail, has a structure that balances generic and application-specific data, and protects the anonymity of the peers whose personal information was captured in monitoring and measurement data. Using two large traces taken from real P2P systems we show evidence of the usefulness of the proposed format, and substantiate the hope that our unified format has the potential to become a standard for sharing P2P traces.