An online scalable algorithm for average flow time in broadcast scheduling

In this paper 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, i.e. (1 + )-speed O(1)-competitive for any fixed > 0. In this paper, we give the first analysis of an online scalable algorithm.