Optimal placement of sensors for network lifetime extension in Wireless Sensor Networks with dynamic routing
Abstract
In recent years, to ensure reliable monitoring and analysis of unknown and untested environments, practitioners have started using Wireless Sensor Networks (WSNs), i.e., collections of tiny disposable, low-power devices, equipped with programmable computing, multiple-parameter-sensing, and wireless communication capacity, able to measure ambient conditions to detect some objects located or events happening around. However, wireless sensor nodes have at the same time some limitations such as low bandwidth, error-prone transmissions, processing and storage capacities, but the most critical is the limitation in energy, which directly affects the network lifetime, making routing in WSNs more demanding compared to Mobile Ad-hoc Networks (MANETs) and cellular networks. Sensor nodes constraints combined with the deployment of a large number of sensors, increase complexity to the design and management of WSNs. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. The focus, however, has been given to the routing protocols which might differ depending on the application and network architecture. When designing a WSN, it is critically important to place the sensors and set up routing protocols in such a way as to maintain connectivity and maximize the network lifetime. In this research, you will find techniques that allow us to optimize the typical deployment of sensors on a field and distribute the energy consumption of the network in such a way that the network lifetime can be maximized under the constraint that connectivity is preserved.
Subject Area
Electrical engineering
Recommended Citation
Barragan, Dante E, "Optimal placement of sensors for network lifetime extension in Wireless Sensor Networks with dynamic routing" (2008). ETD Collection for University of Texas, El Paso. AAI1456738.
https://scholarworks.utep.edu/dissertations/AAI1456738