Underwater Acoustic Sensor Networks (UASN) has driven a lot of attention from researchers because of advancements in sensor technology and unexplored applications of the ocean. UASNs monitor the targeted area with heterogeneous underwater sensors and relay that information to the onshore sink node in mission-critical applications. It is very much essential to know the source of information whenever some critical events happened in the UASNs. Hence, to learn the source of information, i.e. finding the location of the sensor node is crucial. To address this issue, in this paper, initially geometrical object such as trapezoid is used to form the clusters in the targeted region. After that, the proposed localization algorithm is applied and it works in three phases. (i) In the first phase, the sink node initiates the trapezoid formation process through Trapezoid Formation Agent (TFA) and divides the whole network into trapezoids of different geometrical shapes by traveling across the linear trajectory and also creates a search data structure. (ii) In the second phase, the sink deploys AUV at a certain depth for patrolling along the linear trajectory and broadcasts real-time location contained beacon messages at specified points through that anchor nodes are localized by using RSSI. (iii) Sink node activates Localization Agent (LA) in the third phase to perform the location identification process at the trapezoids by using the trilateration method. This work addresses the inherent localization issue of UASNs algorithms and hence it applies to the applications which consider the localization issue. This proposed scheme is well supported by node agencies and knowledgebase. The proposed scheme is simulated in C and validated by different performance parameters.
Localization in Underwater Acoustic Sensor Networks using Trapezoid
