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Topology Mapping. Bo Sheng Sept. 15. Outline. Overview Solutions LTM ACE Problems and discussion Conclusion. Introduction. Topology mapping Mismatch between overlay and physical infrastructure Topology optimization. Introduction. Traffic problem Facts

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## Topology Mapping

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**Topology Mapping**Bo Sheng Sept. 15**Outline**• Overview • Solutions • LTM • ACE • Problems and discussion • Conclusion**Introduction**• Topology mapping • Mismatch between overlay and physical infrastructure • Topology optimization**Introduction**• Traffic problem • Facts • 95% of any pairs of Gnutella nodes are within 7 hops • 50,000 nodes generate 1G/second, 330T/month • Reasons • Blind flooding • Cycles, merge of multiple paths, neighbors exchange • Topology problem • Multiple times over a physical link**Introduction**• Perfect match S S Network infrastructure Overlay network**Introduction**• Mismatch N3 N1 4 5 2 3 S S 2 5 4 N2 Network infrastructure Overlay network**Topology Mismatch**• Problems • Randomly choosing neighbors • Logically close, but physically far away S P N1 N2**Topology Mismatch**• Problems • Unnecessary traffic • Inefficient utilization of bandwidth • Only 2%~5% Gnutella connections link nodes within a single AS (autonomous system) • More than 40% Gnutella nodes are located within top 10 AS • Delayed response • Do we need long-distance neighbors?**Topology Mismatch**• Solutions to traffic problem • Selective flooding • Topology optimization • Avoid cycles • Mapping For each message, how many times it is delivered over a single physical link?**Performance Metrics**• Traffic cost • Search scope • Response time • Overhead**Approaches**• Location-aware Topology Matching (LTM), INFOCOM 2004 • Adaptive Connection Establishment (ACE), ICDCS 2004**LTM**• Three main operations • TTL-2-detector flooding • Message format • Short Source IP& timestamp • Long Source IP& timestamp, TTL1 IP& timestamp • d(i,S,v) • Link cost IP(S),T(S) S N1 N2 IP(S),T(S) IP(N1),T(N1) d(i,S,1) d(i,S,0)**LTM**• Three main operations • Low productive connection cutting • Case1: P receives d(i,S,1) and d(i,S,0) S N P will-cut list**LTM**• Three main operations • Low productive connection cutting • Case2: P receives multiple d(i,S,0) S N1 N2 P**LTM**• Three main operations • Low productive connection cutting • Case3: P receives one d(i,S,1) and multiple d(i,S,0) S N1 N2 P cut list**LTM**• Three main operations • Source peer probing S N1 P**LTM**Step2.case2 S S Step3 N1 N1 N2 P P**LTM**Step2.case3 Step2.case2 S S N1 N1 N2 N2 P P Step2.case3 Step2.case1**LTM**Step3 S S Step2.case1 N1 N1 P P**LTM**• States Case2 Case1 Case3 Step3**LTM**• Performance • Traffic • Search scope • Overhead**ACE**• Step1: • Probe link costs with neighbors • Build neighbor cost table • Exchange neighbors cost table with neighbors**ACE**• Step2: • Create a minimum spanning tree among each peer and its neighbors E E 14 14 4 4 15 G G S S 6 6 20 F F**ACE**• Step3: • Replace neighbors Case1: SH<SG E Case2: GH>SH>SG 14 4 Case3: SH>SG,SH>GH G S 6 H F**ACE**• Depth of optimization (h-neighbor closure) A 15 10 D 20 B 8 12 14 C E 7 A->B=10 A->D=15 E->C=7 E->D=14 B->E=8 D->E=14 Total:68**ACE**• 2-neighbor closure A A 15 10 D D 20 B B 8 12 14 C E C E 7 A->B=10 B->E=8 E->C=7 E->D=14 Total:39**Discussion**• Measurement • Link cost is not accurate • Link cutting and cycles • Heuristic to theoretical support • f (Pn,Tn)=?**Conclusion**• Importance • Effectiveness vs. cost • Future work

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