N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST DHT Based P2P (Peer-to-Peer) for Exploiting Network Proximity ChanMo Park Jan. 9, 2004

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 2/20 Contents  Problems  Estimating Internet Distance  Exploiting Topology Information  Approaches towards exploiting network proximity  Discussion

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 3/20 Problems  P2P File Sharing  DHT (Distributed Hash Table) Based Approaches oCAN ( ’01 - ACIRI) oChord (’01 - MIT ) oTapestry (’01 - Berkeley) oPastry (’01 - Microsoft)  What can help P2P File Sharing? oPerformance of DHT based P2P  Routing (Lookup and Insert)  Nearest node as Next hop  Exploiting Network Proximity

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 4/20 Estimating Internet Distance  Triangulated Heuristic ’00 USC  IDMaps ’01 University of Michigan  GNP (Global Networking Positioning) ’02 CMU  Vivaldi ’03 MIT (Chord)

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 5/20 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 Base nodes A B

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 6/20 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 A B Tracer 1 Tracer 2 a b c

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 7/20 GNP (Global Network Positioning)’02 - CMU

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 8/20 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 oSimulating 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 oCollecting latency information from only a few other hosts oPiggy-backing latency information on application traffic

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 9/20 Exploiting Topology Information  Proximity Routing  Proximity Neighbor Selection  Geographic layout

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 10/20 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 ro uting  Adv. oLight weight, easy to implement oWorkable for all algorithms  Limitation oImprovement depend on number of neighbor.

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 11/20 Proximity Neighbor Selection  Proximity criterion is applied when choosing neighbors, not just when choosing the next hop  Topology  constructing Routing Table  Adv. oImprove performance for prefix routing  Limitation oCan Not apply to CAN, Chord, etc.

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 12/20 Geographic layout  Geographical layout is to choose node identifiers in a geographically informed manner.  Choose nodeID according to physical network  Adv. oSuccessfully apply to CAN  Limitation oNot apply to one dimensional ID space overlay (Chord, Tapestry, P astry, etc) oNeed landmark oDestroy uniform ID population  Load balance

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 13/20 Approaches towards exploiting network proximity 1.Efficient Topology-Aware Overlay Network ’02 2.Efficient Topology-Aware Overlay Network ’02 3.Exploiting network proximity in peer-to-peer overlay networks ’02 4.Topology-aware routing in structured peer-to-peer overlay networks ’02 5.Topologically-Aware Overlay Construction and Server Selection ’02 6.Building Topology-Aware Overlays using Global Soft-State ’03

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 14/20 Efficient Topology-Aware Overlay Network ’02(#1)  Mithos  Proximity Neighbor Selection  Efficient routing o Cartesian coordinate system o Irregular hypercube mesh  Locality-preserving o Chose neighbors wisely  Routing and forwarding o Quadrant-based o Only neighbors known o Efficient forwarding  Assuming 2-D oConnect to each quadrant oForward according to destination vector oRouting becomes trivial

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 15/20 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

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 16/20 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 oEach 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

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 17/20 Topologically-Aware Overlay Construction and Server Selection ’02  Based on CAN  Distributed Binning oRequire a set of landmark node spread across the Internet oSelect a particular bin by Measuring its distance to a set of landmarks oUsing Landmark ordering oPartition the coordinate space into m! equal sized portions

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 18/20 Building Topology-Aware Overlays using Global Soft-State ’03  eCAN  Landmark clustering + RTT oComputers with similar landmark vectors are likely to be close omeasures RTT to top candidates to find the nearest neighbor oUse landmark vector as the DHT key U Landmark vector U=(u1,u2,u3,u4) L1L2L3L4 Landmark nodes u1u2u3u4 V Landmark vector V=(v1,v2,v3,v4) v1v2v3v4 U’ Landmark space Landmark vector B A

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 19/20 Discussion

N ETWORKed M EDIA L AB. D EPT. OF I NFO. & C OMM., K-JIST 20/20 References 1.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))Building Topology-Aware Overlays using Global Soft-State" 2.S. Ratnasamy, M. Handley and R. Karp, “Topologically-Aware Overlay Construction and Server Selection”, Proceedings of Infocom, 2002(CAN Geographic Layout)Topologically-Aware Overlay Construction and Server Selection 3.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 (Pastry Proximity Neighbor) SelectionTopology-aware routing in structured peer-to-peer overlay networks 4.Exploiting network proximity in peer-to-peer overlay networks. Miguel Castro, Peter Druschel, Y. Charlie Hu, and Antony Rowstron. Technical report MSR-TR , 2002 (Pastry Proximity Neighbor Selection)Exploiting network proximity in peer-to-peer overlay networks. 5.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, triangulationMarcel WaldvogelEfficient Topology-Aware Overlay Network Hot Topics in Networks I (HotNets-I)Computer Communication Review triangulation