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Evaluation of the Proximity between Web Clients and their Local DNS Servers

Evaluation of the Proximity between Web Clients and their Local DNS Servers. Z. Morley Mao Chuck Cranor, Fred Douglis, Misha Rabinovich, Oliver Spatscheck, and Jia Wang. Motivation – originator problem. Originator problem CDNs assume that clients are close to their local DNS servers

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Evaluation of the Proximity between Web Clients and their Local DNS Servers

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  1. Evaluation of the Proximity between Web Clients and their Local DNS Servers Z. Morley Mao Chuck Cranor, Fred Douglis, Misha Rabinovich, Oliver Spatscheck, and Jia Wang

  2. Motivation – originator problem • Originator problem • CDNs assume that clients are close to their local DNS servers • Content Distribution Networks (CDNs) • Try to deliver content from servers close to users • Current server selection mechanisms • Uses Domain Name System (DNS) Verify the assumption that clients are close to their local DNS servers

  3. Measurement setup • Three components • 1x1 pixel embedded transparent GIF image • <img src=http://xxx.rd.example.com/tr.gif height=1 width=1> • A specialized authoritative DNS server • Allows hostnames to be wild-carded • An HTTP redirector • Always responds with “302 Moved Temporarily” • Redirect to a URL with client IP address embedded

  4. 1. HTTP GET request for the image 2. HTTP redirect to IP10-0-0-1.cs.example.com Client [10.0.0.1] Redirector for xxx.rd.example.com 7. HTTP GET request for the image 8. HTTP response 6. Reply: content server IP address 3. Request to resolve IP10-0-0-1.cs.example.com Content server for the image 4. Request to resolve IP10-0-0-1.cs.example.com 5. Reply: IP address of content server Name server for *.cs.example.com Local DNS server Embedded image request sequence

  5. Measurement data/stats

  6. Proximity metrics: • AS clustering • Observes if client and LDNS belong to the same AS • Network clustering • Network cluster based on BGP routing information using longest prefix match • Observes if client and LDNS belong to the same network cluster • Roundtrip time correlation • Correlation between message roundtrip times from a probe site to the client and its LDNS server • Probe site represents a potential cache server location • A crude metric, highly dependent on the probe site

  7. client Local DNS server Proximity metric:traceroute divergence (TD) Probe machine • Use the last • point of divergence • TD=Max(3,4)=4 • Sample Probe sites: • NJ(UUNET), NJ(AT&T), • Berkeley(calren), Columbus(calren) • size: 48,908 client-LDNS pairs • Median divergence: 4 • Mean divergence: 5.8-6.2 • Ratio of common to disjoint path length • About 66% pairs traced have common path at least as long as disjoint path a b 1 1 2 2 3 3 4

  8. Proximity analysis results:AS, network clustering • AS clustering: coarse-grained • Network clustering: fine-grained • Most clients not in same routing entity as their LDNS • Clients with LDNS in same cluster slightly more active • Numbers in red indicate improvement possible.

  9. Impact on commercial CDNs • total # clients = 3,234,449 • Verifiable client: A client with LDNS in cluster, responding to our request, and has at least one cache server in its cluster • Majority of “misdirected clients” for NAC have LDNS nonlocal

  10. Conclusion • DNS based server selection works well for coarse-grained load-balancing • Server selection can be inaccurate if cache server density is high • Future work • Study alternatives to DNS based server selection • Improved proximity evaluation

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