Using pathchar to estimate Internet link characteristics
SIGMETRICS '99 Proceedings of the 1999 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
ACM Transactions on Computer Systems (TOCS)
User-level internet path diagnosis
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
An algebraic approach to network coding
IEEE/ACM Transactions on Networking (TON)
Circumventing Server Bottlenecks: Indirect Large-Scale P2P Data Collection
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
NetProfiler: profiling wide-area networks using peer cooperation
IPTPS'05 Proceedings of the 4th international conference on Peer-to-Peer Systems
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Division-of-labor between server and P2P for streaming VoD
Proceedings of the 2012 IEEE 20th International Workshop on Quality of Service
On replication algorithm in P2P VoD
IEEE/ACM Transactions on Networking (TON)
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Recent studies show that network coding improves multicast session throughput. In this paper, we demonstrate how random linear network coding can be incorporated to provide network diagnosis for peer-to-peer systems. We present a new trace collection protocol that allows operators to diagnose peer-topeer networks. It is essential to monitor large-scale peer-to-peer applications by collecting measurements referred to as snapshots from the peers. However, existing solutions are not scalable and fail to collect measurements from peers that departed before the time of collection. We use progressive random linear network coding to disseminate the snapshots in the network, from which the server pulls data in a delayed fashion. We leverage the power of progressive encoding to increase block diversity and tolerate extreme block losses by introducing redundancy in the network. Peers cooperate by allocating cache capacity for other peers. Snapshots of departed peers can thus be retrieved from the network. We show how our protocol controls the redundancy introduced through progressive encoding and thus scales to large number of peers and tolerates high level of peer dynamics.