relative network positioning via cdn redirections

Ao-Jan Su, David R. Choffnes,Fabián E. Bustamante andAleksandar Kuzmanovic

Department of EECSNorthwestern University

Relative Network Positioning via CDN Redirections

IEEE ICDCS 2008

Relative Network Positioning via CDN Redirections Ao-Jan Su

Network PositioningWhy do we need network positioning systems?– Emerging large scale distributed systems can

benefit from selecting among alternative nodes• Example: select an on-line gaming server

– All-to-all measurements are not scalable

Current approaches – Provide network positioning services in a scalable

way (e.g. landmark based)– Clear tradeoffs

• Precision vs. overhead• Precision vs. deployment• And others

2


ObservationsContent distribution networks (e.g., Akamai) improve web performance by– Performing extensive network measurements– Redirecting clients to their closest replica servers– Publishing the results through DNS

3

Can we reuse those measurements collected by CDNs to build a network positioning system?

Relative Network Positioning via CDN Redirections Ao-Jan Su4

CDNs Basics

Web client’s request redirected to ‘close’ by server– Client gets web site’s DNS CNAME entry with domain name

in CDN network– Hierarchy of CDN’s DNS servers direct client to 2 nearby

servers

Internet

Web client

Hierarchy of CDN DNS servers

Customer DNS servers

(1)

(2)

(3)

(4)(5)

(6)

LDNSClient requests translation for yahoo

Client gets CNAME entry with domain name in Akamai

Client is given 2 nearby web replica servers (fault tolerance)

Web replica serversMultiple redirections to find nearby edge servers


Our approachCDN-based Relative Network Positioning (CRP)Clients are redirected to currently closest replica servers in generalCDN’s redirections are primarily driven by network conditions (latency) [Su et al. 2006]Inferring relative network distance by overlapping CDN replica servers

5

A B C

R1 R2


Uses of CRPClosest node selection– Select the closest node (shortest latency) from a

group of candidates (e.g. select the closest on-line gaming server)

– Methodology• Encode redirection frequency from a node to its redirected

replica servers by a vector• Compare similarity (cosine similarity) of nodes’ redirection

vectors to estimate proximity

6Client

Server A

Server B

Replica servers R1

R2

R3

0.8

0.2


Uses of CRP (Cont.)Clustering– Select a set of nodes that are close to each other

(e.g. replicate content to a group of nodes)– Methodology

• Select cluster centers• Assign strong mapping peers to the cluster centers

7


Evaluation GoalsComparing the performance of CRP’s closest node selection to – Ground truth – active measurements– A state of the art network positioning system –

Meridian [Wong 2005]

With respect to– Accuracy– Scalability– Deployment– Overhead

8Meridian: Closest node selection


Experiment SetupGlobally distributed nodes– 1000 DNS servers as clients– 240 Planet Lab nodes as candidate servers (on the

same nodes as our reference system – Meridian)

Concurrent data collection– Monitoring CDN redirections by recursive DNS

queries for CRP– Querying Meridian via its interface– Measuring end-to-end latencies by pings as the

ground truth

9


Selecting the closest node

10

Clients are not close to any servers due to • Limited Planet Lab nodes coverage (Meridian)• Located in areas not well served by CDNs (CRP)

CRP’s accuracy is comparable to its alternative without active measurements and dedicated infrastructure

CRP’s recommendations for 65% of nodes differ from Meridian by < 7ms

CRP outperforms Meridian by 25% of the nodes due to larger deployment of CDN replica servers


Selecting the closest node (Cont.)Relative Error: estimated latency – ground truth

11

80% of CRP nodes have relative error < 50ms

CRP’s is quite accurate comparing to ground truth, with virtually no measurement overhead


Rank: rank 0 is the closest server

Load on CDN’s DNS System

12

Low probe frequency • Smaller overhead• Less accurate• Miss overlapping replica servers

100 mins probe frequency• Appropriate for 95% of nodes• Much less than CDN’s DNS TTL (20 secs)• Overhead is too small to impact CDN’s operations

High probe frequency • Can Improve accuracy• Larger overhead


Load on CRP Clients

13

Large history • More refined results• Larger computation overhead

Small history• Sufficient for CRP • Small overhead• Capture network dynamics


You May Be Wondering“Will CDNs be unhappy because of CRP?”– CRP nodes behaves as regular web clients– CRP’s overhead does not impact CDN’s daily

operations– Could be an additional service provided by CDNs

“What if CDNs change their redirection policy?”– CRP’s goal aligns with CDNs– Our approach is not restricted to a specific CDN,

CRP can reuse results from other measurement infrastructures

14


SummaryCRP discovers relative positions of end hosts– Closest node selection– Clustering

Key features of CRP– Accurate– Light-weight

• Reuse CDN’s network measurements

– Scalable• No dedicated infrastructure is required

15


Cosine Similarity

16

relative network positioning via cdn redirections

Documents