Capacity-insensitive algorithms for online facility assignment problems on a line
Abstract
In the online facility assignment problem , there exist servers on a metric space where each has an integer capacity and a request arrives one-by-one. The task of an online algorithm is to irrevocably match a current request with one of the servers with vacancies before the next request arrives. As special cases for , we consider on a line , which is denoted by and , where the latter is the case of with equidistant servers. In this paper, we perform the competitive analysis for the above problems. As a natural generalization of the greedy algorithm grdy, we introduce a class of algorithms called MPFS (Most Preferred Free Servers) and show that any MPFS algorithm has the capacity-insensitive property, i.e., for any MPFS algorithm alg for , if alg is -competitive when , then alg is -competitive for general . By applying the capacity-insensitive property of the greedy algorithm grdy, we derive the matching upper and lower bounds on the competitive ratio of grdy for . To investigate the capability of MPFS algorithms, we show that the competitive ratio of any MPFS algorithm alg for is at least . Then, we propose a new MPFS algorithm idas (Interior Division for Adjacent Servers) for and show that the competitive ratio of idas for is at most , i.e., idas for is best possible in all the MPFS algorithms. We also give numerical experiments to investigate the performance of idas and grdy and show that idas performs better than grdy for distribution of request sequences with locality.
Communicated by Dachuan Xu