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DHT Based P2P (Peer-to-Peer) for Exploiting Network Proximity. ChanMo Park cmpark@netmedia.kjist.ac.kr Jan. 9, 2004. Contents. Problems Estimating Internet Distance Exploiting Topology Information Approaches towards exploiting network proximity Discussion. Problems. P2P File Sharing
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DHT Based P2P (Peer-to-Peer) for Exploiting Network Proximity ChanMo Park cmpark@netmedia.kjist.ac.kr Jan. 9, 2004
Contents • Problems • Estimating Internet Distance • Exploiting Topology Information • Approaches towards exploiting network proximity • Discussion
Problems • P2P File Sharing • DHT (Distributed Hash Table) Based Approaches • CAN ( ’01 - ACIRI) • Chord (’01 - MIT ) • Tapestry (’01 - Berkeley) • Pastry (’01 - Microsoft) • What can help P2P File Sharing? • Performance of DHT based P2P • Routing (Lookup and Insert) • Nearest node as Next hop • Exploiting Network Proximity
Estimating Internet Distance • Triangulated Heuristic ’00 USC • IDMaps ’01 University of Michigan • GNP (Global Networking Positioning) ’02 CMU • Vivaldi ’03 MIT (Chord)
Base nodes A B Triangulated Heuristic ’00 USC • Select N nodes in the network to be base nodes • A node H is assigned coordinates (N-tuples) which are the distances between H and the N base nodes • Then the distance between H1 and H2 is bounded below by bounded above by • U, L, or (U+L)/2 can be distance estimation
Tracer 1 a b A c B Tracer 2 IDMaps ’01 Univ. of Michigan • Special HOPS servers maintain a virtual topology map of the Internet consisting of end hosts and Tracers • Distance of host A and B is estimated as D=a+b+c
Vialdi’03 - MIT • Distributed algorithm assigning synthetic coordinates in D-dimensional space to Internet hosts • Predicting latency between two hosts by Euclidean distance between their coordinates • Coordinate of each node • Simulating node’s position in a network of physical network • Sampling the network latency between each node and a few other nodes, adjusting the node’s coordinates to minimize the error between the predicted and sampled latencies. • No fixed infrastructure • Collecting latency information from only a few other hosts • Piggy-backing latency information on application traffic
Exploiting Topology Information • Proximity Routing • Proximity Neighbor Selection • Geographic layout
Proximity Routing • Proximity routing is when the routing choice is based not just which neighboring node makes the most progress towards the key, but is also based on which neighboring node is closest in the sense of latency. • compromise between progress in the ID space and proximity in routing • Adv. • Light weight, easy to implement • Workable for all algorithms • Limitation • Improvement depend on number of neighbor.
Proximity Neighbor Selection • Proximity criterion is applied when choosing neighbors, not just when choosing the next hop • Topology constructing Routing Table • Adv. • Improve performance for prefix routing • Limitation • Can Not apply to CAN, Chord, etc.
Geographic layout • Geographical layout is to choose node identifiers in a geographically informed manner. • Choose nodeID according to physical network • Adv. • Successfully apply to CAN • Limitation • Not apply to one dimensional ID space overlay (Chord, Tapestry, Pastry, etc) • Need landmark • Destroy uniform ID populationLoad balance
Approaches towards exploiting network proximity • Efficient Topology-Aware Overlay Network ’02 • Efficient Topology-Aware Overlay Network ’02 • Exploiting network proximity in peer-to-peer overlay networks ’02 • Topology-aware routing in structured peer-to-peer overlay networks ’02 • Topologically-Aware Overlay Construction and Server Selection ’02 • Building Topology-Aware Overlays using Global Soft-State ’03
Efficient Topology-Aware Overlay Network ’02(#1) • Mithos • Proximity Neighbor Selection • Efficient routing • Cartesian coordinate system • Irregular hypercube mesh • Locality-preserving • Chose neighbors wisely • Routing and forwarding • Quadrant-based • Only neighbors known • Efficient forwarding • Assuming 2-D • Connect to each quadrant • Forward according to destination vector • Routing becomes trivial
Efficient Topology-Aware Overlay Network ’02 (#2) • Node ID cannot be known a priori • Find out during join phase • Descend towards global minimum • Stabilize using "spring forces" • Result: Node ID
Exploiting network proximity in peer-to-peer overlay networks ’02 Topology-aware routing in structured peer-to-peer overlay networks ’02 • Pastry (Tapestry) • Proximity Neighbor Selection • Using mechanism to build routing tables taking network proximity into account • Proximity Invariant • Each entry in a node X’s routing table refers to a node that is near X, according to the proximity metric, among all the live Pastry nodes with the appropriate nodeID prefix
Topologically-Aware Overlay Construction and Server Selection ’02 • Based on CAN • Distributed Binning • Require a set of landmark node spread across the Internet • Select a particular bin by Measuring its distance to a set of landmarks • Using Landmark ordering • Partition the coordinate space into m! equal sized portions
Landmark vector U=(u1,u2,u3,u4) A U’ U Landmark space Landmark nodes L1 L2 L3 L4 u1 u2 u3 u4 v1 v2 v3 v4 Landmark vector B Landmark vector V=(v1,v2,v3,v4) V Building Topology-Aware Overlays using Global Soft-State ’03 • eCAN • Landmark clustering + RTT • Computers with similar landmark vectors are likely to be close • measures RTT to top candidates to find the nearest neighbor • Use landmark vector as the DHT key
References • Zhichen Xu, Chunqiang Tang, and Zheng Zhang: "Building Topology-Aware Overlays using Global Soft-State". The 23rd International Conference on Distributed Computing Systems. May 19-22, 2003 Providence, Rhode Island USA (CAN Proximity Neighbor Selection (Landmark + RTT)) • S. Ratnasamy, M. Handley and R. Karp, “Topologically-Aware Overlay Construction and Server Selection”, Proceedings of Infocom, 2002(CAN Geographic Layout) • Miguel Castro, Peter Druschel, Y. Charlie Hu, and Antony Rowstron. “Topology-aware routing in structured peer-to-peer overlay networks“, In FuDiCo 2002: International Workshop on Future Directions in Distributed Computing. University of Bologna Residential Center Bertinoro (Forli), Italy, June 2002. (Pastry Proximity Neighbor) Selection • Exploiting network proximity in peer-to-peer overlay networks. Miguel Castro, Peter Druschel, Y. Charlie Hu, and Antony Rowstron. Technical report MSR-TR-2002-82, 2002 (Pastry Proximity Neighbor Selection) • Marcel Waldvogel and Roberto Rinaldi, “Efficient Topology-Aware Overlay Network”, Hot Topics in Networks I (HotNets-I), October 2002.The HotNets-I proceedings will also appear in Computer Communication Review, Volume 33, Number 1, January 2003, http://www.cs.washington.edu/hotnets/papers/waldvogel.pdf ,Delaunay triangulation