MODELING OF THE MODIFIED SSLE IN OPNET FOR LARGE SCALE WIRELESS SENSOR NETWORKS

Location information along with sensed data is important for most of the applications in wireless sensor networks (WSNs). This paper presents a modified sectoral sweeper based localization estimation (SSLE) method which is improved version of our previously studied SSLE method and it's modeling in OPNET. This technique requires simplified message formats. Only a central node which needs to have smart antenna processing capability estimates locations of sensor nodes. The modified SSLE is modeled using OPNET modeler with log-normal shadowing effects. The present OPNET wireless module uses standard log-distance model without any shadowing effects. We add log-normal shadowing effects by providing a user with ability to choose variance of shadowing effects from 0 dB to 5 dB according to the wireless environment. The detailed implementation methodology in OPNET is presented in terms of node and process models. The performance of modified SSLE is evaluated through different network and channel parameters in terms of localization error and average throughput. The simulation results show that the modified SSLE method can achieve with 9.5% average localization error under log normal shadowing channel conditions.