RISN: An Efficient, Dynamically Tasked and Interoperable Sensor Network Overlay

EUC(2010)

引用 1|浏览21
暂无评分
摘要
Sensor network has given rise to a comprehensive view of various environments through their harnessed data. Usage of the data is, however, limited since the current sensor network paradigm promotes isolated networks that are statically tasked. In recent years, users have become mobile entities that require constant access to data for efficient processing. Under the current limitations of sensor networks, users would be restricted to using only a subset of the vast amount of data being collected, depending on the networks they are able to access. Through reliance on isolated networks, proliferation of sensor nodes can easily occur in any area that has high appeals to users. Furthermore, support for dynamic tasking of nodes and efficient processing of data is contrary to the general view of sensor networks as subject to severe resource constraints. Addressing the aforementioned challenges requires the deployment of a system that allows users to take full advantage of data collected in the area of interest to their tasks. In light of these observations, we introduce a hardware-overlay system designed to allow users to efficiently collect and utilize data from various heterogeneous sensor networks. The hardware-overlay takes advantage of FPGA devices and the mobile agent paradigm in order to efficiently collect and process data from cooperating networks. The computational and power efficiency of the system are herein demonstrated.
更多
查看译文
关键词
comprehensive view,hardware-overlay system,dynamically tasked,efficient processing,current sensor network paradigm,harnessed data,sensor node,process data,sensor network,various heterogeneous sensor network,interoperable sensor network overlay,constant access,base stations,ubiquitous computing,wireless sensor networks,system design,power efficiency,data collection,fpgas,fpga,sensors,hardware,prototypes,field programmable gate arrays,mobile agent,mobile computing,sensor networks
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要