期刊名称：Electronic Colloquium on Computational Complexity
印刷版ISSN：1433-8092
出版年度：2010
卷号：2010
出版社：Universität Trier, Lehrstuhl für Theoretische Computer-Forschung
摘要：In this paper we study a dynamic version of capacity maximization in the physical model of wireless communication. In our model, requests for connections between pairs of points in Euclidean space of constant dimension d arrive iteratively over time. When a new request arrives, an online algorithm needs to decide whether or not to accept the request and to assign one out of k channels and a transmission power to the channel. Accepted requests must satisfy constraints on the signal-to-interference-plus-noise (SINR) ratio. The objective is to maximize the number of accepted requests.
Using competitive analysis we study algorithms using distance-based power assignments, for which the power of a request relies only on the distance between the points. Such assignments are inherently local and particularly useful in distributed settings. We first focus on the case of a single channel. For request sets with spatial lengths in [1] and duration in [1] we derive a lower bound of (d2) on the competitive ratio of any deterministic online algorithm using a distance-based power assignment. Our main result is a near-optimal deterministic algorithm that is Missing \right-competitive, for any constant 0.
Our algorithm for a single channel can be generalized to k channels. It can be adjusted to yield a competitive ratio of Ok1k(d2k)+ for any factorization (kk) such that kk=k. This illustrates the effectiveness of multiple channels when dealing with unknown request sequences. In particular, for (loglog) channels this yields an O(loglog)-competitive algorithm. Additionally, we show how this approach can be turned into a randomized algorithm, which is O(loglog)-competitive even for a single channel. Finally, we show the robustness of our results by extending all upper bounds from Euclidean to doubling metrics.
