Robustness of time-division schedules for Internet broadcast
Kevin E. Foltz, Jehoshua Bruck · 2003
The model we consider consists of a server and many clients. The clients have a large incoming bandwidth and little or no outgoing bandwidth. The server repeatedly broadcasts information through the air to the clients. There are two information items with lengths l/sub 1/ and l/sub 2/, and demand probabilities p/sub 1/ and p/sub 2/. The demand probability of an item is simply the relative frequency of requests for that item by the clients, scaled such that the sum of the p/sub i/'s is 1. These items contain static data. This allows us to receive data out of order and use parts of different broadcasts to reassemble items. The metric we use to evaluate broadcast schedules is expected waiting time. This is the expected time a client must wait for an item, averaged over all items and clients, with weight p/sub i/ for item i.