1. Travis Portz

2.  Large, sudden increases in the traffic to a website  Low-traffic website being linked to by a popular news feed  “Slashdot Effect”  Popular news sites receiving increased traffic due to a major world event  Effects of flash crowd  Reduced performance  Website inaccessible

3.  Content distribution network (CDN)  Embedded objects stored on external servers  Commercial solutions are expensive for low-traffic websites  Drop requests  Not a real solution  Proposed alternative:  Web servers collaborate in a peer-to-peer content distribution network

5.  Estimate request arrival rate λ for each object on the web server  Exponential moving average  Similar to TCP’s estimation of RTT

6. CONTENT REPLICATION  If arrival rate exceeds λ R, start replicating content on peer servers  Make one copy for each request received  Stop when all peers have copies REQUEST FORWARDING  If arrival rate exceeds λ F, start forwarding requests to peer servers  HTTP redirection  Round-robin order

7.  Not all requests are forwarded once arrival rate exceeds λ F  Origin server handles some requests, forwards other requests with probability P F  Probability increases with  Request arrival rate  Time since last request forwarded to peer server

8.  Inputs  List of servers and structure of overlay network  Baseline request rates  Request rates for flash crowd objects  Server bandwidth and processing limits

9.  Outputs  Actual server request rates  Request drop rates  Bandwidth usage