Energy-scalable algorithms and protocols for wireless microsensor networks

Wireless microsensor networks lend themselves to trade-offs in energy and quality. In these networks, the individual sensor data per se is not necessarily important to the end user. Rather, it is the combined knowledge of all the sensors that describes what is occurring in the environment. By allowing the algorithms and protocols to adapt the quality of this description, with a corresponding change in energy dissipation, sensor networks can be flexible to the end-user's requirements. In this paper, we provide models for predicting quality and energy and show the advantages of trading off these two parameters. By ensuring that the system operates at a minimum energy for each quality point, the system can achieve both flexibility and energy efficiency, allowing the end-user to maximize system lifetime.