Game theory based hybrid localization technique for underwater wireless sensor networks

• Published in: Transactions on emerging telecommunications technologies 2022-11, Vol.33 (11), p.n/a
• Main Authors: Kumar, Manni, Goyal, Nitin, Qaisi, Ramy Mohammed Aiesh, Najim, Mohd, Gupta, Sachin Kumar
• Format: Article
• Language: English
• ISSN: 2161-3915; 2161-3915
• DOI: 10.1002/ett.4572

In an underwater environment, it is necessary but tough to track the location of deployed sensor nodes because of node's mobility, nonavailability of GPS, node software or hardware failure and so forth. Due to these reasons, nodes cannot directly communicate with enough beacons in the neighbourhoods, resulting into localization error. This creates the need to develop the range‐based localization method that takes into consideration the features of the underwater environment with precise location estimation. The existing range‐based localization techniques involve huge computational and storage overhead along with localization latency. To solve these problems, a hybrid localization estimation technique of received signal strength (RSS) and angle of arrival (AoA) is presented in this article. In this hybrid method, AoA is estimated from the primary anchor (PA) while RSS is measured from the selected set of secondary anchors (SAs). Further, Game theory model is also applied to considerably increase the precision by choosing the optimum set of SAs even in the mobility assisted underwater environment. The proposed technique of identifying unknown sensor nodes is tested through NS2 simulation with multiple runs. The proposed technique achieves minimum localization error, delay, energy consumption and high packet delivery ratio in comparison to topology control for energy‐efficient localization, game theory based routing protocol, iterative mobile target localization, and RSS‐based localization. Proposed node localization scheme increase the accuracy by conjointly considering RSS and AoA measurements. Game theory model is applied to select optimum secondary anchors for throughput and energy efficiency enhancement. Localization error and latency is minimized by reducing storage overhead even with the presence of node mobility.