Hybrid multi objective localization strategy in wireless sensor network using different optimization algorithms

Abstract

A Wireless Sensor Network (WSN) is a system made up of a huge newlineamount of sensor nodes that are wirelessly linked together to monitor, detect, newlineand gather data from a physical region of interest. WSNs have been utilized in newlinea diversity of solicitations in recent years due to their lesser dimension, low newlinecost, and ease of usage. Healthcare, military, agricultural, object monitoring, newlineunderwater, and a variety of other applications are examples of such newlineapplications. The sensed data is important in most of these applications, and newlinethe whereabouts of this data is essential to take further action. A basic newlineexample is the precise location of a fire source or the location of pollution. newlineBecause many WSNs are positioned in an indiscriminate manner, with nodes newlinespread at random points, it is necessary to distribute each node with its unique newlinelocation manually. As a result, alternative efficient approaches are required to newlinecomplete such a process. newlineWhen it emanates to the actual applications, WSNs are associated newlinewith only a few limitations. Noise and changes in the environment, and also newlinemulti - path fading, continue to be a threat to range facts. Because it demands newlinethe placement of additional nodes for sensing range information, this has a newlinesignificant impact on energy utilization and overall price component. These newlineconcerns led the door for new localization methods, as well as some machine newlinelearning-based non-linear localized methods for dealing with noise issues newlinehave been presented. newline