Local coverage measurement algorithm in GPS-free wireless sensor networks

Coverage preservation during a mission is a crucial issue for wireless sensor networks (WSNs). There are numerous methods to measure the coverage globally, such as circular, grid and non-circular models, but only a few algorithms can be used to measure the coverage locally, using a sensor. A local coverage measurement algorithm uses only the location of a sensor and its neighbors to calculate the coverage, either by having the location information or by determining this information. Absolute localization for location-based services determines sensor positions according to the global Cartesian coordinate system, usually with the help of a global positioning system (GPS) device. In some applications, such as local coverage measurement, the sectional position of neighbors related to a sensor is sufficient. For a GPS-free environment, this paper develops a local position estimation algorithm (LPEA), using triangulation rules, which contains estimation and estimation correction procedures. Simulation results demonstrated that the algorithm is superior to previous work on finding the exact location of neighbors. Moreover, the estimation error in finding the location of neighbors in a 100-m wide field is less than 5 m whenever a minimum of eight neighbors is available. Furthermore, measuring coverage using the results of this LPEA is nearly identical to results where the locations of all sensors are known. In this paper, the circular model, the Delaunay triangulation (DT) coverage measurement model, was used, where the circular model, the circular model with shadowing effect and the circular probabilistic model are measurable through a DT coverage measurement. Simulation and real device experiments indicated that the algorithm is significantly accurate in terms of the local coverage measurement and accelerates the operation in coverage measurement algorithms in wireless sensor networks.