CRI: ENSL: Experimental Network of Sensors Lab for advancing research in sensed-data collection, integration, management, and analysis?

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Proposal #: CNS 07-09437PI(s): Soliman, Handy S. Liebrock, Lorie M.; Mazumdar, Subhasish; Mukkamala, Srinivas; Shin, DongwanInstitution: New Mexico Institute of Mining and Technology Socorro, NM 87801-4796Title: ENSL: Experimental Network of Sensors Lab for Advancing Research in Sensed-Data Collection, Integration, Management, and AnalysisThis project, building a multi-tier network in 4 layers, aims to tackle problems related to the acquisition and analysis of data from a network of sensors with the premise that the network topology and the data processing hierarchy should be matched. Thus, as data from sensor nodes moves to leader nodes in the field and thence to more powerful data collection nodes, it gets transformed in phases: from data to information (e.g., data aggregation), then from information to knowledge (e.g., spatial and temporal trends), and finally from knowledge to intelligence, i.e., decisions (based on soft computing and other models plus analysis of past decisions). Tiers 1 through 4 describe the hierarchy and associate them with different computing power, connectivity, and research problems. Tiers 1 and 2 will focus on energy-aware transmission between nodes, develop a security framework for sensors, study and apply fusion techniques, and experiment with network protocols. Nodes at Tiers 3 and 4 will be used to dynamically control the operations of Tiers 1 and 2 sensors, e.g., by altering cryptographic parameters based on risk analysis, and by changing transmission requirements to promote energy preservation while trading off data quality. The powerful multi-processor Tier 4 nodes will be used to experiment with simulations and data mining algorithms that result in the decisions about the sensed data, and about the environment of the network itself (e.g., intrusion detection). This Tier will also provide visualization, a critical resource for comprehension and abstraction of the full sensor network.Broader Impacts: Enabling cross-fertilization of ideas from networking, data management, visualization, parallel computing, security, and data mining, the project creates new tools and software components for researchers. ENSL will also introduce new courses and enrich those existing. Moreover, summer courses are planned to reach high school students.