Building Quality-of-Information Aware Distributed Sensing SystemsNSF CNS-1566374 |
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Award InformationThis website is based upon work supported by the National Science Foundation under grant CNS-1566374. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. |
Project Background and GoalsThe proliferation of increasingly capable and affordable sensing devices that pervade every corner of the world has given rise to distributed sensing systems that have fundamentally changed people's ways of interacting with the physical world. Despite their tremendous benefits, distributed sensing systems pose great new research challenges, of which one important facet stems from the conflicts between the Quality of Information (QoI) provided by the sensor nodes and the consumption of system and network resources. On one hand, individual sensors are not reliable, due to various reasons such as incomplete observations, background noise, and poor sensor quality. To address this problem, a possible solution is to integrate information from multiple sensors that observe the same events, as this will likely cancel out the errors of individual sensors. On the other hand, distributed sensing systems usually have limited resources (e.g., bandwidth, energy, storage, etc). Therefore, it is usually prohibitive to collect data from a large number of sensors due to the potential excessive resource consumption. Targeting on this challenge, this project seeks to develop a resource-efficient information integration framework that can intelligently integrate information from distributed sensors so that the highest quality of information can be achieved, under the constraint of system resources. |
Project ImpactThis project will lead to method development, analysis, and system prototypes for quality-of-information aware distributed sensing systems, which have the following broader impacts: 1) The development of the QoI aware information integration framework in this project will help address growing research challenges for the collection, transmission and analysis of massive sensory data. 2) The proposed QoI aware resource allocation mechanisms will advance the state-of-the-art in both physical and crowd sensing system research by addressing novel challenges brought by constrained system resources. 3) Successful completion of the proposed research will benefit a whole spectrum of applications that have tremendous natural and societal impact, including environment monitoring, military surveillance, smart transportation, urban sensing, health care, spectrum sensing, and many others. We expect the outputs of this project can inspire new research ideas in not only computer science but also many other disciplines such as transportation engineering, industrial engineering, animal and environmental science, and social science. 4) The research results will be integrated into course materials and K-12 outreach activities, and thus can benefit a large group of students, especially the female and minority students. |
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