Self-Organization in Ad Hoc Sensor Networks: An Empirical Study

摘要

Research in classifying and recognizing complex concepts has been directing its focus increasingly on distributed sensing using a large amount of sensors. The colossal amount of sensor data often obstructs traditional algorithms in centralized approaches, where all sensor data is directed to one central location to be processed. Spreading the processing of sensor data over the network seems to be a promising option, but distributed algorithms are harder to inspect and evaluate. Using self-sufficient sensor boards with short-range wireless communication capabilities, we are exploring approaches to achieve an emerging distributed perception of the sensed environment in real-time through clustering. Experiments in both simulation and real-world platforms indicate that this is a valid methodology, being especially promising for computation on many units with limited resources.