Abstract
Designers of content distribution networks (CDNs) often need to determine how changes to infrastructure deployment and configuration affect service response times when they deploy a new data center, change ISP peering, or change the mapping of clients to servers. Today, the designers use coarse, back-of-the-envelope calculations or costly field deployments; they need better ways to evaluate the effects of such hypothetical 'what-if' questions before the actual deployments. This paper presents What-If Scenario Evaluator (WISE), a tool that predicts the effects of possible configuration and deployment changes in content distribution networks. WISE makes three contributions: 1) an algorithm that uses traces from existing deployments to learn causality among factors that affect service responsetime distributions; 2) an algorithm that uses the learned causal structure to estimate a dataset that is representative of the hypothetical scenario that a designer may wish to evaluate, and uses these datasets to predict hypothetical response-time distributions; 3) a scenario specification language that allows a network designer to easily express hypothetical deployment scenarios without being cognizant of the dependencies between variables that affect service response times. Our evaluation, both in a controlled setting and in a real-world field deployment on a large, global CDN, shows that WISE can quickly and accurately predict service response-time distributions for many practical what-if scenarios.
Original language | English (US) |
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Article number | 6449271 |
Pages (from-to) | 1-13 |
Number of pages | 13 |
Journal | IEEE/ACM Transactions on Networking |
Volume | 21 |
Issue number | 1 |
DOIs | |
State | Published - 2013 |
All Science Journal Classification (ASJC) codes
- Software
- Computer Science Applications
- Computer Networks and Communications
- Electrical and Electronic Engineering
Keywords
- Causality
- Web performance
- What-If Scenario Evaluator (WISE)
- content distribution network (CDN)