Abstract: In Wireless Sensor Networks (WSNs), a node location is usually estimated using GPS or network localization algorithms, but this estimation incurs some errors. In this work, we propose techniques to improve node locations and reduce the location errors. Location errors have an impact on location-based routing algorithms. Packets could be delayed in reaching the destination, or dropped due to exceeding the hop count. Altogether, this drains the energy resource of WSNs. Our techniques to reduce the location errors are as follows: First, a node identifies a subset of its neighboring nodes that have estimated Euclidian distances greater than the given communication range as OutLier (OL) nodes. A node can communicate with OL nodes because their unknown actual locations are within the communication range, but their estimated locations are not. We use, then, mathematical formulas to correct the OL locations to be within the communication range and thus close to their actual locations. This OL method works for a binary sensor model in which the radio signal strength cannot be measured, and the system works on the binary values Received or Not Received. If the sensor model can measure the radio signal strength, then in addition to the OL method, we can use a Received Signal Strength Indicator (RSSI) to calibrate the distance and to reposition the OL nodes. We call this approach OutLiers with Calibration (OLC). Finally, we incorporate our derived mathematical equations into our simulation. The simulation results show that OL and OLC reduce the miss probability of an actual next node, which means better location of the next node.
