On the Randomized Competitive Ratio of Reordering Buffer Management with Non-Uniform Costs

Abstract

Reordering buffer management (RBM) is an elegant theoretical model that captures the tradeoff between buffer size and switching costs for a variety of reordering/sequencing problems. In this problem, colored items arrive over time, and are placed in a buffer of size $k$. When the buffer becomes full, an item must be removed from the buffer. A penalty cost is incurred each time the sequence of removed items switches colors. In the non-uniform cost model, there is a weight $w_c$ associated with each color $c$, and the cost of switching to color $c$ is $w_c$. The goal is to minimize the total cost of the output sequence, using the buffer to rearrange the input sequence.

Recently, a randomized $O(\log \log k)$-competitive online algorithm was given for the case that all colors have the same weight (FOCS 2013). This is an exponential improvement over the nearly tight bound of $O(\sqrt{ \log k})$ on the deterministic competitive ratio of that version of the problem (Adamaszek et al. , STOC 2011). In this paper, we give an $O((\log \log k\gamma )^2)$-competitive algorithm for the non-uniform case, where $\gamma$ is the ratio of the maximum to minimum color weight. Our work demonstrates that randomness can achieve exponential improvement in the competitive ratio even for the non-uniform case.

Sungjin Im—Supported in part by NSF grant CCF-1409130.