Peer-to-peer computing is an interesting networking paradigm as it offers a high degree of scalability by exploiting the resources of the participants and avoids single-points of failures. Due to these desirable properties, peer-to-peer computing plays a crucial role in many networking applications beyond file-sharing, and the underlying ideas are also discussed as a design principle for the future Internet. Our research is concerned with the question of whether peer-to-peer is mature enough to step outside its "comfort zone". We conduct measurements of state-of-the-art peer-to-peer networks such as Kad and investigate the robustness, e.g., to Sybil attacks or selfish behavior. For example, we implemented the proof-of-concept BitTorrent client "BitThief " which provides evidence that despite the tit-for-tat incentive mechanism, free-riding is possible in BitTorrent. We develop algorithms to improve the performance of peer-to-peer systems: we devise peer-to-peer networks which are robust to worst-case churn (see e.g., our IPTPS paper), which allow for efficient joins and leaves (see e.g., our SHELL system at ICALP), or which are robust to denial of service attacks (see e.g., our Chameleon system at SPAA). Some of these algorithms were successfully implemented in the online storage tool Wuala and the streaming tool Streamforge, two Swiss startups.
|Author||Locher, Thomas and Meier, Remo and Schmid, Stefan and Wattenhofer, Roger|
|Title of Book||21st International Symposium on Distributed Computing (DISC)|
|Address||Berlin / Heidelberg, Germany|
|Series||Lecture Notes in Computer Science (LNCS)|
|Abstract||In contrast to peer-to-peer file sharing, live streaming based on peer-to-peer technology is still awaiting its breakthrough. This may be due to the additional challenges live streaming faces, e.g., the need to meet real-time playback deadlines, or the increased demands on robustness under churn. This paper presents and evaluates novel neighbor selection and data distribution schemes for peer-to-peer live streaming. Concretely, in order to distribute data efficiently and with minimal delay, our algorithms combine low-latency push operations along a structured overlay with the flexibility of pull operations. The protocols ensure that all peers are able to obtain the required data blocks of a live stream in time, and that due to the loop-free dissemination paths, the overhead is low.|