Evaluation of The Prunning and Threshold level Effects on the Localization Error in Secure Localization in WSNs

In terrestrial wireless sensor networks, many of applications need to be aware of the position of the nodes. For example, the report of an event, tracking a moving object, or monitoring physical conditions of an area are some types of applications that the position and coordinates of the referred phenomenon are vital for them. On the other hand, in hostile environments, misleading information can be broadcasted in the network. Thus, without considering a misleading information cancelation procedure, sensor positioning leads to inaccurate estimation. In this paper, we consider a secure localization algorithm based on gradient descending approach with a selective pruning step to remove the misleading information. Then, we describe the effect of the dimensions of the network, the pruning and threshold level on the localization error in the terrestrial networks with noncoordinated and coordinated attacks. The simulation results show that we can find the optimized parameters to obtain minimum error localization.