Fast sensor identification technology for sea surface salinity measurement

In the sea surface salinity (SSS) application, the data collected by the buoys need to be uploaded as the satellite passes through. Fast sensor identification is a novel technique that can be employed to underpin fair and efficient media access in the SSS application. It deviates from the existing conventional media access control schemes including the random access algorithms and out-of-band signaling methods. These approaches do not take advantage of the possible prediction of the buoy locations. Hence, the valuable time is wasted on resolving collisions. In this paper, we propose a fast sensor identification algorithm that allows the satellite to quickly discover the buoys in its footprint. The upload bandwidth can be granted to the buoys once they are identified. We assume a ground data or control center can provide buoy distribution to the satellite. Armed with this information, the proposed algorithm constantly builds optimal query trees for buoy discovery. The tree is constructed so that it will be fast to confirm the buoys which are expected to be in the area. The tree will also be flexible to accommodate prediction errors. That is, it will find all buoys in the satellite´s coverage area. By computer simulations, we compare the proposed algorithm against other automatic identifying techniques such as the binary tree algorithm (BTA) and the query tree algorithm (QTA). It is shown that our approach can reduce the number of reading requirement by the satellite for sensor identification.