An online scalable algorithm for average flow time in broadcast scheduling

Abstract

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.