In this article, the online pull-based broadcast model is considered. In this model, there are n pages of data stored at a server and requests arrive for pages online. When the server broadcasts page p, all outstanding requests for the same page p are simultaneously satisfied. We consider the problem of minimizing average (total) flow time online where all pages are unit-sized. For this problem, there has been a decade-long search for an online algorithm which is scalable, that is, (1 + ε)-speed O(1)-competitive for any fixed ε > 0. In this article, we give the first analysis of an online scalable algorithm.
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