| dc.description.abstract | Identifying the position of the sensor nodes is an important issue in the practical
applications of wireless sensor networks (WSN). In the environment, there are many
factors influencing to node position estimation, increasing the possibility of error rate.
Localization in WSN helps to address the position of the sensor nodes. With the
information from localization, there are many factors are explored such as energy map
generation, node addressing or geographic routing. Therefore, localization is an
important point leading to the success of WSN
Localization can be achieved by two main techniques: range based and range
free. With the advantages of higher accuracy and lower energy, Range-free is considered
as efficient techniques to estimate node position due to bringing low cost and higher
accuracy. In this study, we would like to focus on DV-Hop, an optimization in range
free method using due to the pros of not depending on any influencing factors in the
environment. We would like to apply two different algorithms to estimate the node
positions from the measurements of DV-Hop: least square and particle swarm
optimization (PSO).
Using PSO in DV-Hop method, the conducted extensively simulation shows the
positive impact of PSO in calculating hop count to identify nodes while using the small
number of sample anchor nodes. The result also asserts that the error rate is improved
when the number of anchors increased. | en_US |
