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

Sensornet将在大范围的地理区域内提供精细的空间粒度的详细测量。提供对数据的访问是一项艰巨的挑战，因为测量的数据分布在整个传感器网络中，并且传感器网络节点之间的通信需要大量稀缺的能源。以数据为中心的抽象现在被视为传感器网络系统的一个基本方面，它提供了对传感器测量的有效访问。在之前的工作中，我们建议Sensornet应用程序将受益于以数据为中心的存储。这样的系统使得能够在大规模传感器网络中进行有效的查询和搜索。然而，以数据为中心的存储对其路由基础设施提出了严格的要求。特别是，以数据为中心的存储是以健壮和高效的路由原语为前提的，该原语允许在传感器中的节点上按名称存储数据。GHTs结合了两种技术，分布式哈希表(DHTs)和地理自组织路由，这两种技术是在两个完全不相关的环境中开发的，即对等系统和自组织无线网络。每种技术在各自的领域都得到了广泛的探索，但在传感器网络的新的、更具挑战性的背景下，这些技术的结合提出了许多新的设计挑战。

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.