SENSORS: Robust and Efficient Data Dissemination for Data-Centric Storage

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Sensornets will provide detailed measurements at fine spatial granularities over large geographic areas. Providing access to the data is a formidable challenge because the measured data are distributed across the entire sensornet and communication between sensornet nodes requires substantial expenditures of scarce energy. Data-centric abstractions are now seen as a fundamental aspect of sensornet systems that provide efficient access to sensor measurements. In prior work, we have suggested that sensornet applications would benefit from data-centric storage. Such systems enable efficient querying and search in large-scale sensornets. However, data-centric storage makes exacting demands on its routing infrastructure. In particular, data-centric storage is predicated on a robust and efficient routing primitive that allows storing data by name at a node in the sensornet.This proposal seeks to investigate the design and development of geographic hash tables (GHTs), a routing primitive for data-centric storage. GHTs bring together two technologies, distributed hash tables (DHTs) and geographic ad-hoc routing, that were developed in two completely unrelated contexts, peer-to-peer systems and ad hoc wireless networks. Each technology has been extensively explored in its respective domain, but the combination of these technologies in the new, and more challenging, context of sensor networks raises many new design challenges.