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Topologically-Aware Overlay Construction and Server Selection Sylvia Ratnasamy, Mark Handly, Richard Karp and Scott Shenker Presented by Shreeram Sahasrabudhe.

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Presentation on theme: "Topologically-Aware Overlay Construction and Server Selection Sylvia Ratnasamy, Mark Handly, Richard Karp and Scott Shenker Presented by Shreeram Sahasrabudhe."— Presentation transcript:

1 Topologically-Aware Overlay Construction and Server Selection Sylvia Ratnasamy, Mark Handly, Richard Karp and Scott Shenker Presented by Shreeram Sahasrabudhe CSE 498 Advanced Networks

2 Motivation The potential benefit by some knowledge of topology for distributed internet applications Improving application-level connectivity Need for solution which is Simple Fast – for the dynamic target systems Distributed – no central point of failure or bottleneck Scalable – for millions of nodes

3 Approach Network Measurement used: Network Latency Non-intrusive Light-weight End-to-end Priorities: (Scalability + Practicality) > Accuracy Binning Scheme Evaluation of the application of this scheme to overlay networks and server selection

4 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) Divide the range of possible latency values into layers (absolute)

5 Scalable? Each node only needs measure with small set of landmarks At a million nodes on the network, refreshing at every hour, each landmark would approximately handle 2700pings/sec. (800Mhz m/c; DNS root servers handle DNS queries at 1600/sec) Better scalability by have multiple nodes at a location act as a single logical landmark.

6 Sanity Check For each node in a bin compute Gain ratio = inter-bin latency / intra-bin latency Ratio = Reduction in Latency = Desirable Algorithm tested on simulated topologies (Transit Stub, Power-law Random Graphs) and internet data (NLANR). Improvement rapidly saturates Gain ratio is affected by the size of the underlying topology

7 Binning Vs (Random, Nearest-Neighbor) Random Binning: Each node selects a bin at random. Nearest Neighbor Clustering: At each iteration, two closest clusters are merged into a single cluster.

8 Construction of Overlays Structured: Nodes are interconnected (at application-level) in a well-defined manner. Content-Addressable Network, Chord, PASTRY, Tapestry Unstructured: Less structured networks End- system multicast, Scattercast. Measurement metric is Latency Stretch: ratio of average inter-node latency on the overlay network to the average inter-node latency on the underlying IP-level network. Latency Stretch = Better!

9 Construction of CAN topologies using Binning Ordering of landmarks is used for binning m landmarks, m! orderings Co-ordinate space divided along first dimension into m portions, each portion sub divided along second dimension into m-1 portions and so on New node joins CAN at a random portion associated with its landmark ordering Result Co-ordinate space not uniformly populated Uneven distribution of size of zone spaces (future work!)

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11 Unstructured Overlays Given a set of n nodes on the Internet, have each node pick any k neighbor nodes from this set, so that the average routing latency on the resultant overlay is low. Use a heuristic algorithm: node picks k/2 closest nodes and k/2 at random Short-Long: Shortest path routing, short-long-short BinShort: k/2 nodes from self-bin and rest k/2 at random.

12 Server - Selection If (Server=bin[client]) > 1 Redirect to a random server in same bin Else Select existing server with most_similar_bin to client’s (Degree of similarity between two bins = no of matches of positions in landmark ordering) Stretch = (latency to selected server) / (latency to optimal server)

13 - For TS-10K 1000 servers, rest clients - Adjusted stretch - For NLANR data - Improved performance - diminishing returns


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