Double Rulings for Information Brokerage in Sensor Networks

We study the problem of information brokerage in sensor networks, where information consumers (sinks, users) search for data acquired by information producers (sources). In-network storage such as geographical hash table (GHT) has been proposed to store data at rendezvous nodes for consumers to retrieve. In this paper, we propose a double rulings scheme that stores data replicas on a curve instead of one or multiple isolated sensors. The consumer travels along another curve that is guaranteed to intersect the producer curve. The double rulings is a natural extension of the flat hashing scheme such as GHTs. It has improved query locality-i.e., consumers close to producers find the data quickly-and structured aggregate queries, i.e., a consumer following a curve is able to retrieve all the data. Furthermore, by the flexibility of retrieval mechanisms, we have better routing robustness (as multiple retrieval paths are available) and data robustness against regional node failures. We show by simulation that the double rulings scheme provides reduced communication costs and more balanced traffic load on the sensors.