Poster Abstract: Is Data-Centric Storage and Querying Scalable?

The scalability of a wireless sensor network has been of interest and importance. We use a constrained optimization framework to derive fundamental scaling laws for both unstructured sensor networks (which use blind sequential search for querying) and structured sensor networks (which use efficient hash-based querying). We find that the scalability of a sensor network’s perfo rmance depends upon whether or not the increase in energy and storage resources with more nodes is outweighed by the concomitant application-specific increase in event and query loads . We have figured out the theoretical scaling laws for the networks of 2 dimensional deployment in our previous work [2]. We report on our work-in-progress aimed at extending the scaling laws to networks of various dimensional deployment. As a recent achievement, we find that m· q 1/2 must be O(N d 1 2d ) for unstructured networks, and