Exact algorithms to minimize interference in wireless sensor networks

AbstractFinding a low-interference connected topology is a fundamental problem in wireless sensor networks (WSNs). The problem of reducing interference through adjusting the nodes’ transmission radii in a connected network is one of the most well-known open algorithmic problems in wireless sensor network optimization. In this paper, we study minimization of the average interference and the maximum interference for the highway model, where all the nodes are arbitrarily distributed on a line. First, we prove that there is always an optimal topology with minimum interference that is planar. Then, two exact algorithms are proposed. The first one is an exact algorithm to minimize the average interference in polynomial time, O(n3Δ), where n is the number of nodes and Δ is the maximum node degree. The second one is an exact algorithm to minimize the maximum interference in sub-exponential time, O(n3ΔO(k)), where k=O(Δ) is the minimum maximum interference. All the optimal topologies constructed are planar

Constructing Minimum-Interference Networks ∗

A wireless ad-hoc network can be represented as a graph in which the nodes represent wireless devices, and the links represent pairs of nodes that communicate directly by means of radio signals. The interference caused by a link between two nodes u and v can be defined as the number of other nodes that may be disturbed by the signals exchanged by u and v. Given the position of the nodes in the plane, links are to be chosen such that the maximum interference caused by any link is limited and the network fulfills desirable properties such as connectivity, bounded dilation or bounded link diameter. We give efficient algorithms to find the links in two models. In the first model, the signal sent by u to v reaches exactly the nodes that are not farther from u than v is. In the second model, we assume that the boundary of a signal’s reach is not known precisely and that our algorithms should therefore be based on acceptable estimations. The latter model yields faster algorithms.