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Data-Centric Active Querying in Sensor Networks: The ACQUIRE Project

Data-Centric Active Querying in Sensor Networks: The ACQUIRE Project. Bhaskar Krishnamachari Co-PI: Ahmed Helmy Department of Electrical Engineering-Systems USC Viterbi School of Engineering bkrishna@usc.edu, helmy@usc.edu Autonomous Networks Research Group http://ceng.usc.edu/~anrg/.

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Data-Centric Active Querying in Sensor Networks: The ACQUIRE Project

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  1. Data-Centric Active Querying in Sensor Networks: The ACQUIRE Project Bhaskar Krishnamachari Co-PI: Ahmed Helmy Department of Electrical Engineering-Systems USC Viterbi School of Engineering bkrishna@usc.edu, helmy@usc.edu Autonomous Networks Research Group http://ceng.usc.edu/~anrg/ NOSS PI Meeting, October 18, 2004

  2. Motivation • Querying is a fundamental operation in wireless sensor networks (WSN) • Project Goal: develop techniques for query resolution and efficient information discovery in WSN

  3. Active Querying • Basic Idea: query entities which move efficiently through the network actively “hunting” for the desired information. • Research Issues: • Framework and algorithms • query guidance • performance analysis and parameter optimization • adaptation and multi-threading • validation and testing

  4. Preliminary Work: ACQUIRE • An active query forwarding mechanism that provides a look-ahead parameter d to tune between the extremes of flooding and trajectory-based querying. Caching is allowed at the intermediate steps. flood trajectory Data Dynamics Parameter Sadagopan, Krishnamachari, Helmy, “Active Query Forwarding in sensor networks,” IEEE SNPA Workshop 2003.

  5. Preliminary Work: RUGGED • Technique for routing based on fingerprint gradients in sensor networks, i.e. using information about spatial pattern of physical phenomena. • Single and multi-path probabilistic forwarding Faruque, Helmy, “RUGGED: RoUting on finGerprint Gradients in sEnsor Networks,” IEEE ICPS 2004.

  6. Expected Contributions • Development of network primitives for active querying that can serve as “building blocks” for a wide range of applications • Insights into performance and design tradeoffs through a combination of mathematical analysis, simulation and experiments NOSS PI Meeting, October 18, 2004

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