The Tenet Architecture for Tiered Sensor Networks
The Tenet Architecture for Tiered Sensor Networks
复制标题
DOI：
10.1145/1777406.1777413
复制
发表时间：
2010-07-01
影响因子：
4.1
通讯作者：
Kohler, Eddie
中科院分区：
文献类型：
--
作者：
Paek, Jeongyeup;Greenstein, Ben;Kohler, Eddie
大多数传感器网络研究和软件设计都遵循一种架构原则，即允许在小尺寸、资源贫乏的节点或微点上进行多节点数据融合。虽然我们是这种方法最早的推动者之一，但通过经验，我们发现这种原则会导致脆弱和难以管理的系统，并探索另一种选择。Tenet架构的动机是观察到未来大规模传感器网络部署将分层，由低层的微节点和上层相对不受约束的32位平台节点组成。Tenet将多节点融合限制在主层，同时允许节点处理本地生成的传感器数据。这简化了应用程序开发，并允许重用底层软件。通过从一个新的微线程库组合任务描述，运行在主任务笔记上的应用程序。我们的Tenet实现还包含一个健壮的、可扩展的网络子系统，用于分发任务和可靠地交付响应。我们展示了一个Tenet追逃应用程序显示了与mote-native实现相当的性能，同时更加紧凑。我们还介绍了Tenet系统的两个实际部署：Vincent Thomas Bridge的结构振动监测应用和James Reserve的基于成像的栖息地监测应用，并展示了分层架构可扩展网络容量并允许可靠的高速率数据传输。（1)
Most sensor network research and software design has been guided by an architectural principle that permits multinode data fusion on small-form-factor, resource-poor nodes, or motes. While we were among the earliest promoters of this approach, through experience we found that this principle leads to fragile and unmanageable systems and explore an alternative. The Tenet architecture is motivated by the observation that future large-scale sensor network deployments will be tiered, consisting of motes in the lower tier and masters, relatively unconstrained 32-bit platform nodes, in the upper tier. Tenet constrains multinode fusion to the master tier while allowing motes to process locally-generated sensor data. This simplifies application development and allows mote-tier software to be reused. Applications running on masters task motes by composing task descriptions from a novel tasklet library. Our Tenet implementation also contains a robust and scalable networking subsystem for disseminating tasks and reliably delivering responses. We show that a Tenet pursuit-evasion application exhibits performance comparable to a mote-native implementation while being considerably more compact. We also present two real-world deployments of Tenet system: a structural vibration monitoring application at Vincent Thomas Bridge and an imaging-based habitat monitoring application at James Reserve, and show that tiered architecture scales network capacity and allows reliable delivery of high rate data.(1)