Ajax Prediction
- 1. Making Magic Happen: Predicting User Behavior in AJAX applications Jonathan Boutelle Uzanto Consulting
- 2. Who am I? www.uzanto.com www.jonathanboutelle.com
- 6. Vanilla Web Application ( circa 2000 ) Http request Initial Html User action Html (with data embedded) User action Html (with data embedded) … HTML Server Dbase User action requiring data User action requiring data
- 7. Rich Internet Application ( circa 2003 ) Http request for app App (ActionScript & Flash) downloads Data UI Client Manager Server Dbase User action requiring data
- 8. Rich Internet Application ( circa 2004 ) Http request for app App (ActionScript & Flash) downloads User action requiring data Optionally preload data UI Client Manager Server Dbase
- 9. AJAX Application ( circa 2005 ) Http request for app User action requiring data ALWAYS preload data UI Client Manager Server Dbase App (Javascript & HTML) downloads
- 11. Building a model of user behavior Build naïve model Validate and refine model Be metric driven Responsiveness: % user data requests that were met with pre-fetched data Efficiency: the % of pre-fetched data that ended up being used
- 13. Download if value > cost Value = value of reduced latency * odds the data will be needed Cost = cost of download * odds the data won’t be needed
- 14. Value vs. Cost
Editor's Notes
- #2: I’d like to start by thanking Jesse and Rail for putting this meeting together. The momentum that has built up since Jesse coined the term AJAX less than two months ago has been really remarkable, and I think it’s really valuable to get us all in the same room so that we can hammer out what it all means, and where things are going from here..