Topology control meets SINR: the scheduling complexity of arbitrary topologies
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Improved Algorithms for Latency Minimization in Wireless Networks
ICALP '09 Proceedings of the 36th Internatilonal Collogquium on Automata, Languages and Programming: Part II
Oblivious interference scheduling
Proceedings of the 28th ACM symposium on Principles of distributed computing
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
The capacity of wireless networks
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
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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 request. 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,Δ] and duration in [1,Γ] we derive a lower bound of 驴(Γ驴Δ d/2) 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 O(Γ驴Δ(d/2)+驴 )-competitive, for any constant 驴0.Our algorithm for a single channel can be generalized to k channels. It can be adjusted to yield a competitive ratio of O(k驴Γ 1/k驴驴Δ(d/2k驴)+驴 ) for any factorization (k驴,k驴) such that k驴驴k驴=k. This illustrates the effectiveness of multiple channels when dealing with unknown request sequences. In particular, for 驴(log驴Γ驴log驴Δ) channels this yields an O(log驴Γ驴log驴Δ)-competitive algorithm. Additionally, we show how this approach can be turned into a randomized algorithm, which is O(log驴Γ驴log驴Δ)-competitive even for a single channel.