Autonomous anomaly detection and molecular signaling framework for synthetic nanodevices

In this study, we are presenting a knowledge harvesting framework that is designed for synthetic nanodevice model presented in Akgül and Canberk (2014). As the model is applied for mobile synthetic devices, the transmission of the harvested data becomes a challenge. A molecular flooding algorithm is also proposed to help the spread of the detected anomalies. In particular, we focus on the blood sugar anomaly, which leads us the performance metric of capability of regulation. The effects of interference and sampling time are investigated in the performance evaluation part.
Source: Nano Communication Networks - Category: Nanotechnology Source Type: research