Distributed in-network data processing aims to reduce energy consumed for communication and establish a self-contained data storage, retrieval, aggregation, and query sensor system. Previous research focuses on two-dimensional (2D) wireless sensor networks where a 2D planar setting is assumed. Compared with sensor networks deployed on 2D plane, it is significantly more challenging to support in-network data processing in three-dimensional (3D) wireless sensor networks. This project aims to explore distributed in-network data storage and retrieval in a 3D wireless sensor network, especially one that is deployed in an irregular region with potential coverage holes.
The proposed research will apply geometric and topological tools to investigate and develop different schemes for constructing geographic hash table-based and double-ruling based information storage and retrieval in general 3D sensor networks. The designed algorithms ensure the success and accuracy of data retrieval, well-balanced load across the network, limited information stored at individual nodes, and distributed operations. A testbed will be established for experimental exploration and evaluation.
This project helps to extend distributed in-network data processing from 2D sensor networks to 3D, in support of a range of future applications in diverse disciplines that demand sensors to be deployed in three dimensional space. It also enriches the engineering curriculum to integrate the theory of computational geometry and topology with practical systems. The PIs will continue the effort in improving female presence in computer science.