A column generation approach to maximize capacity of multi-rate power controlled TDMA wireless sensor networks

Abstract

This paper describes a mixed-integer linear programming model to maximize wireless sensor networks (WSN) capacity by determining traffic routes and target coverage, adjusting data rates, and dynamically controlling transmission power. Radio transmissions are studied under signal-to-interference-plus-noise-ratio (SINR) model. In the considered WSN, a set of targets needs to be continuously monitored by a given number of already deployed sensors. The objective is to gather as much sensing data as possible during a unit time period. Since this type of problems is known to be NP-hard, we propose a computationally feasible column generation based approach to find near-optimal solutions when dealing with integer flow and coverage variables. Extensive computational experiments even show that optimal solutions are reached in most cases for reasonable network sizes. Numerical results illustrate the benefits from extending the number of available transmission power levels, the major impact of data rate adaptation on throughput, and demonstrate that achieving higher network capacity comes at the expense of deploying more sensors than the minimum required to connectivity and target monitoring. © 2013 Springer-Verlag.