Handling churn in a DHT

This paper addresses the problem of churn--the continuous process of node arrival and departure--in distributed hash tables (DHTs). We argue that DHTs should perform lookups quickly and consistently under churn rates at least as high as those observed in deployed P2P systems such as Kazaa. We then show through experiments on an emulated network that current DHT implementations cannot handle such churn rates. Next, we identify and explore three factors affecting DHT performance under churn: reactive versus periodic failure recovery, message timeout calculation, and proximity neighbor selection. We work in the context of a mature DHT implementation called Bamboo, using the ModelNet network emulator, which models in-network queuing, cross-traffic, and packet loss. These factors are typically missing in earlier simulation-based DHT studies, and we show that careful attention to them in Bamboo's design allows it to function effectively at churn rates at or higher than that observed in P2P file-sharing applications, while using lower maintenance bandwidth than other DHT implementations.

[1]  Scott Shenker,et al.  Epidemic algorithms for replicated database maintenance , 1988, OPSR.

[2]  B. Pittel On spreading a rumor , 1987 .

[3]  V. Jacobson,et al.  Congestion avoidance and control , 1988, SIGCOMM '88.

[4]  Rajmohan Rajaraman,et al.  Accessing Nearby Copies of Replicated Objects in a Distributed Environment , 1997, SPAA '97.

[5]  Ellen W. Zegura,et al.  A quantitative comparison of graph-based models for Internet topology , 1997, TNET.

[6]  Peter Druschel,et al.  Pastry: Scalable, distributed object location and routing for large-scale peer-to- , 2001 .

[7]  Ben Y. Zhao,et al.  An Infrastructure for Fault-tolerant Wide-area Location and Routing , 2001 .

[8]  Stefan Saroiu,et al.  A Measurement Study of Peer-to-Peer File Sharing Systems , 2001 .

[9]  Mark Handley,et al.  A scalable content-addressable network , 2001, SIGCOMM '01.

[10]  David R. Karger,et al.  Wide-area cooperative storage with CFS , 2001, SOSP.

[11]  Antony I. T. Rowstron,et al.  Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems , 2001, Middleware.

[12]  David R. Karger,et al.  Chord: A scalable peer-to-peer lookup service for internet applications , 2001, SIGCOMM '01.

[13]  Ben Y. Zhao,et al.  Tapestry: An Infrastructure for Fault-tolerant Wide-area Location and , 2001 .

[14]  Jacky C. Chu,et al.  Availability and locality measurements of peer-to-peer file systems , 2002, SPIE ITCom.

[15]  David R. Karger,et al.  Analysis of the evolution of peer-to-peer systems , 2002, PODC '02.

[16]  Dejan Kostic,et al.  Scalability and accuracy in a large-scale network emulator , 2002, CCRV.

[17]  Ben Y. Zhao,et al.  Brocade: Landmark Routing on Overlay Networks , 2002, IPTPS.

[18]  Frank Dabek,et al.  Learning euclidean coordinates for internet hosts , 2002 .

[19]  Ben Y. Zhao,et al.  Distributed Object Location in a Dynamic Network , 2002, SPAA '02.

[20]  Peter Druschel,et al.  Exploiting network proximity in peer-to-peer overlay networks , 2002 .

[21]  David Mazières,et al.  Kademlia: A Peer-to-Peer Information System Based on the XOR Metric , 2002, IPTPS.

[22]  Josh Cates,et al.  Robust and efficient data management for a distributed hash table , 2003 .

[23]  Stefan Savage,et al.  Understanding Availability , 2003, IPTPS.

[24]  Krishna P. Gummadi,et al.  Measurement, modeling, and analysis of a peer-to-peer file-sharing workload , 2003, SOSP '03.

[25]  Rodrigo Rodrigues,et al.  Proceedings of Hotos Ix: the 9th Workshop on Hot Topics in Operating Systems Hotos Ix: the 9th Workshop on Hot Topics in Operating Systems High Availability, Scalable Storage, Dynamic Peer Networks: Pick Two , 2022 .

[26]  Krishna P. Gummadi,et al.  The impact of DHT routing geometry on resilience and proximity , 2003, SIGCOMM '03.

[27]  Helen J. Wang,et al.  An evaluation of scalable application-level multicast built using peer-to-peer overlays , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[28]  Scott Shenker,et al.  Building a flexible and efficient routing infrastructure: Need and chal-lenges , 2003 .

[29]  Miguel Castro,et al.  Controlling the Cost of Reliability in Peer-to-Peer Overlays , 2003, IPTPS.

[30]  Robert Tappan Morris,et al.  Designing a DHT for Low Latency and High Throughput , 2004, NSDI.

[31]  Jia Wang,et al.  Analyzing peer-to-peer traffic across large networks , 2002, IMW '02.

[32]  Ben Y. Zhao,et al.  Tapestry: a resilient global-scale overlay for service deployment , 2004, IEEE Journal on Selected Areas in Communications.

[33]  Robert Tappan Morris,et al.  Comparing the Performance of Distributed Hash Tables Under Churn , 2004, IPTPS.

[34]  Miguel Castro,et al.  Performance and dependability of structured peer-to-peer overlays , 2004, International Conference on Dependable Systems and Networks, 2004.

[35]  Ion Stoica,et al.  The Case for a Hybrid P2P Search Infrastructure , 2004, IPTPS.

[36]  Mark Handley,et al.  Datagram Congestion Control Protocol (DCCP) , 2006, RFC.