Inventive approach of path planning mechanism for mobile anchors in WSN

Recently, Wireless Sensor Network has become a fast growing research area in the field of communication. Sensor Networks find applications in various areas of communication like acoustic detection, medical monitoring, detection of forest fire, and surveillance of military movements. These applications are essential in order to update the captured data with the locally transmitted information. Quite fittingly, anchor node has been evolved to enable locating the exact position of sensor nodes in the absence of GPS in each node. However, mobile anchor node fills the requirement by covering the sensing area at lesser cost. Localization is an essential issue in wireless sensor networks because many applications require the sensor nodes to know their locations with a high degree of precision. Various localization methods based on mobile anchor nodes have been proposed for assisting the sensor nodes to determine their locations. However, none of these methods attempt to optimize the trajectory of the mobile anchor node. Generally, with regard to localization algorithm, only single mobile anchor is customized for identifying the location and to receive the data by sensing. In this paper, a mechanism with two mobile anchors is proposed by using specified exact trajectory known as Z-curve. In this method, two mobile anchors are designed to move along both the directions for localizing the sensor node and transmit/broadcast the data sensed. Hence the use of two mobile anchors attains optimal localization in comparatively shorter duration. The simulation results derived from this study proves better performance of the proposed path planning method than the existing methods.

Automated summary

Wireless Sensor Networks have applications in various communication areas, and localization is crucial for sensor nodes to know their precise locations. Mobile anchor nodes, especially with a mechanism using two anchors, can achieve optimal localization in a shorter time, proving to be more effective than existing methods.