Efficient corona training protocols for sensor networks

Phenomenal advances in nano-technology and packaging have made it possible to develop miniaturized low-power devices that integrate sensing, special-purpose computing, and wireless communications capabilities. It is expected that these small devices, referred to as sensors, will be mass-produced and deployed, making their production cost negligible. Due to their small form factor and modest non-renewable energy budget, individual sensors are not expected to be GPS-enabled. Moreover, in most applications, exact geographic location is not necessary, and all that the individual sensors need is a coarse-grain location awareness. The task of acquiring such a coarse-grain location awareness is referred to as training. In this paper, two scalable energy-efficient training protocols are proposed for massively-deployed sensor networks, where sensors are initially anonymous and unaware of their location. The training protocols are lightweight and simple to implement; they are based on an intuit...

• Type: Journal
• Year: 2008
• Where: TCS
• Authors: Alan A. Bertossi, Stephan Olariu, Maria Cristina Pinotti
• Keywords: Coarse-grain Location Awareness, Individual Sensors, Sensor, TCS 2008, Theoretical Computer Science