Randomized Online Computation with High Probability Guarantees.

We study the relationship between the competitive ratio and the tail distribution of randomized online problems. To this end, we identify a broad class of online problems for which the existence of a randomized online algorithm with constant expected competitive ratio r implies the existence of a randomized online algorithm that has a competitive ratio of ( 1 + ε ) r with high probability , measured with respect to the optimal profit or cost, respectively. The class of problems includes some of the well-studied online problems such as paging, k -server, and metrical task systems on finite metric spaces.