传感器网络中的协同存储管理
Collaborative Storage Management In Sensor Networks
摘要：
在本文中，我们考虑一类传感器网络，其中的数据是不需要在实时的观察员，例如，传感器网络监测的科学现象，以后播放和分析。在这样的网络中，数据必须存储在网络中。因此，除了电池电源，存储是主要资源：网络的使用寿命受到其存储生成的数据样本的能力的限制。我们探索使用协同存储技术，有效地管理数据存储受限的传感器网络。所提出的协同存储技术利用附近传感器收集的数据之间的空间相关性，以显着减少数据源附近的数据的大小。我们表明，所提出的方法提供了显着的节省存储数据的大小与本地缓冲，允许网络运行更长的时间，而不会耗尽存储空间，并减少最终将被中继到观察者的数据量。此外，如果数据生成速率在传感器之间不一致（如在事件驱动传感器网络中的情况），或者如果可用存储在网络之间变化，则协作存储执行可用存储空间的负载均衡。
英文摘要：
In this paper, we consider a class of sensor networks where the data is not required in real-time by an observer; for example, a sensor network monitoring a scientific phenomenon for later play back and analysis. In such networks, the data must be stored in the network. Thus, in addition to battery power, storage is a primary resource: the useful lifetime of the network is constrained by its ability to store the generated data samples. We explore the use of collaborative storage technique to efficiently manage data in storage constrained sensor networks. The proposed collaborative storage technique takes advantage of spatial correlation among the data collected by nearby sensors to significantly reduce the size of the data near the data sources. We show that the proposed approach provides significant savings in the size of the stored data vs. local buffering, allowing the network to run for a longer time without running out of storage space and reducing the amount of data that will eventually be relayed to the observer. In addition, collaborative storage performs load balancing of the available storage space if data generation rates are not uniform across sensors (as would be the case in an event driven sensor network), or if the available storage varies across the network.
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