Polynomial-Based Linear Programming Relaxation of Sensor Network Localization Problem

T. Tamba, Y. Y. Nazaruddin
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Abstract

One important task in the deployment of a wireless sensor network is solving the sensor network localization problem to assure location awareness of each sensor node in the network. The sensor network localization can be formulated as a global optimization problem that aims to minimize the squared inter–sensor distances under the constraint that such distances equal to some given numbers. The corresponding optimization formulation is generally nonsmooth, nonconvex, and NP-hard problem, and thus prior works have proposed approximate solution using relaxation methods such as semidefinite or conic programming. In this paper, a linear programming relaxation approach is proposed to solve such an optimization problem using the concept of Handelman’s representation of nonnegative polynomial functions over polytopic set. Numerical simulation results are given to illustrate the promising potential of the proposed approach.
传感器网络定位问题的多项式线性规划松弛
无线传感器网络部署的一个重要任务是解决传感器网络的定位问题,以保证网络中每个传感器节点的位置感知。传感器网络定位可以表述为一个全局优化问题,其目标是在约束条件下,使传感器间距离的平方最小,且这些距离等于给定的数。相应的优化公式一般是非光滑的、非凸的、np困难的问题,因此先前的工作已经提出了使用半定或二次规划等松弛方法的近似解。本文利用Handelman非负多项式函数在多边形集上的表示的概念,提出了求解这类优化问题的线性规划松弛方法。数值模拟结果说明了该方法的应用前景。
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