Auto-localization algorithm for mobile sensor nodes in wireless sensor networks

In wireless sensor networks, location information is crucial to effectively use the event information recorded by the sensors. However, localizing mobile sensor nodes in resource-constrained networks presents several challenges, including determining the optimal number of anchor nodes, handling mobility, designing a path loss model, considering network topology, and addressing scalability and the number of localized nodes. To overcome these challenges, this paper proposes a coordinate-based auto-localization algorithm (CALA) with a single anchor node for mobile sensor nodes. The proposed algorithm uses an analytical model to determine the location of the target node by considering a parallel coordinate system and retrieving the original location of the target node by moving it to two different locations. The algorithm uses received signal strength indicator (RSSI) values for distance calculation while considering Rayleigh fading in the path loss model. The proposed algorithm's performance is evaluated using various parameter settings, including mobility, node density, fading, path loss exponent, and different random seed values. The study finds that fading and path loss significantly influence the localization process, leading to an accuracy range of 10 to 30% when measuring distances using RSSI. The proposed method shows a 30% improvement in localization accuracy when the number of nodes increases from 5 to 20, achieving an average localization accuracy of 90% in a network with 20 sensor nodes. Furthermore, the study offers an in-depth investigation of the effect of various random generating situations on localization accuracy. Overall, the proposed algorithm offers a promising solution to the challenges of localizing mobile sensor nodes in resource-constrained networks.