1 / 17

Topologically-Aware Overlay Construction and Server Selection

Topologically-Aware Overlay Construction and Server Selection. Sylvia Ratnasamy, Mark Handley, Richard Karp, Scott Shenker Presented by Yun,Jeong-Han. Introduction. Use some knowledge of topology for distributed internet applications Improving application-level connectivity Binning strategy

karik
Download Presentation

Topologically-Aware Overlay Construction and Server Selection

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Topologically-Aware Overlay Construction and Server Selection Sylvia Ratnasamy, Mark Handley, Richard Karp, Scott Shenker Presented by Yun,Jeong-Han

  2. Introduction • Use some knowledge of topology for distributed internet applications • Improving application-level connectivity • Binning strategy • Nodes that fall within a given bin are relatively close to one another in terms of network latency • Simple, scalable, distributed • (Scalability + Practicality ) > Accuracy • Evaluation of the application • Overlay network construction • Server selection

  3. Distributed Binning • Requires a set of landmark machines spread across the internet (8~12 machines) • Nodes measure RTT to each of these landmarks and orders the landmarks in increasing RTT (relative) • Level 0, 1, 2

  4. Distributed Binning : Test • Test topologies • TS-10K and TS-1K • Transit-Stub topologies with 10,000 and 1,000 nodes respectively • PLRG1 and PLRG2 • Power-Law Random Graph with 1166 and 1779 nodes • NLANR (National Laboratory for Applied Network Research) • Data set with the RTT between 103 active monitor • The Key parameters affecting performance are • Type and scale of topology • Number of levels • Number of landmark • Number of nodes being binned

  5. Distributed Binning : Test 1 • The effect of increasing number of levels • 3 level system is suffice in practice • Gain ratio TS-1K Average gain ratio 4.06 TS-10K PLARG2 PLARG1 NLANR Number of levels

  6. Distributed Binning : Test 2 • The effect of increasing number of landmarks • # of bin saturated around 8 landmarks (except TS-10K) TS-1K Average gain ratio TS-10K NLANR PLARG1 PLARG2 Number of landmarks

  7. Distributed Binning : Test 3 • Comparison of different binning schemes • Random binning • Lower bound • No locality • Nearest-neighbor clustering • Upper bound • Requires global knowledge • Landmark-based binning • Close to upper bound C-TS-1K B-TS-1K Average gain ratio C-PLRG1 B-PLRG1 RANDOM Number of landmarks

  8. Scalable? • Just needs measure with small set of landmarks • Each landmark handles 2700 pings/sec • At a million nodes on the network • Refreshing at every hour, • DNS root servers handle DNS queries at 1600/sec • for Better scalability • by having multiple nodes at a location act as a single logical landmark • Ex. 10 machines are one logical landmark

  9. Topologically-aware Construction of Overlay Networks • Two types of overlay networks • Structured overlays • Nodes are interconnected in some well-defined manner at the application level • ex. CAN • Unstructured overlays • Unstructured mesh • Ex. End-system multicast and Scatter-case • Latency stretch

  10. Topologically-sensitiveCAN Construction

  11. Topologically-sensitiveCAN Construction RANDOM Average latency stretch #Landmark=4 Average latency stretch #Landmark=8 RANDOM #Landmark=12 #Landmark=4 #Landmark=8 #Landmark=12 Number of overlay nodes Number of overlay nodes

  12. Topologically-aware Construction of Unstructured Overlays • Optimal construction is NP-hard • Short-long algorithm • A node with k neighbors, pick k/2 nodes closest to itself and another k/2 nodes at random • Need global knowledge, does not scale • BinShort-long algorithm • Pick k/2 nodes at random from its own bin • BinShort-long algorithm with sampling • Pick k/2 nodes closest to itself from its own bin 5 Average latency stretch RANDOM BSL BSL-S SL Number of overlay nodes

  13. Topologically-aware Server Selection • Parameters to select a good server • Server load and distance (network latency) • Select a random server from its own bin or closest bin • The client includes its bin information in a DNS query • DNS name server maintains the bin information of content server • 3 other selection scheme • Random • Based on Cartesian distance • Using the Hotz metric • Latency stretch

  14. Topologically-aware Server Selection • 12 landmarks and 3 levels • Number of servers • TS-10K : 1000 • TS-1K, PLRG1 and PLRG2 :100 • NLANR : 10 • All the above simple topological hint works well • Binning scheme is more scaleable

  15. Topologically-aware Server Selection • Effect of number of landmarks and topologies • Increasing landmarks improves performance • Slight performance improvement for PLRGs • Most nodes within a few(2~4) hops TS-10K Average latency stretch TS-1K PLRG2 PLRG1 8 Number of landmarks

  16. Topologically-aware Server Selection • Cumulative distribution of the latency stretch for TS-10K • 10,000 nodes, 1,000 server, 12 landmarks, 3 levels • Cartesian distance and Binning based selection yield better results BINING CARTESIAN Percentage of nodes Hotz random Latency Stretch

  17. Conclusions • A simple, scalable, binning scheme that can be used to infer network proximity information • Apply this scheme to overlay construction and server selection • Coarse-grained topological information can significantly improve application performance • Using actual Internet traces • A few landmarks yield significant improvements

More Related