A Search-Efficient Architecture for Data-Centric Sensor Networks

In data-centric sensor networks, sensor data is not necessarily forwarded to a central sink for storage; instead, the nodes themselves serve as a distributed in-network storage, collectively storing sensor data and waiting to answer user queries. A key problem in designing such a network is how to map data and queries to their corresponding rendezvous nodes so that a query can find its matching data quickly and efficiently. Existing techniques are mostly aimed to address a certain type of queries. The capability to support queries of any type is desirable, yet remains a challenge. We propose a search-efficient architecture for data-centric sensor networks, that can simultaneously address range queries and top-k, the two most popular query types. Importantly, the proposed technique does not require location information, hence applicable to a wide range of sensor networks. Our theoretical findings are complemented by a simulation-based evaluation.