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Dynamic Deployment strategies in Ad-Hoc Sensor networks to optimize Coverage and Connectivity in Unknown Event Boundary detection

Venkataraman, Aparna
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1313773833

Abstract Details

2011, MS, University of Cincinnati, Engineering and Applied Science: Computer Science.
There are many ways to geographically determine the boundary of an event based on its location and its nature through Satellite imaging and other learning mechanisms. In these methods, the availability of resources to perform the detection, their capabilities, actual time available to determine the event and its accessibility are constraints. At times, the satellite images may not be sufficient to get complete information about an event. Here we consider a particular case where the aim is to detect the actual boundary of an event based on its estimated boundary with the above constraints. A typical situation would be to determine the actual boundary of fire given the smoke area, or to estimate the concentration of chemical content, ideally any situation where sensors need to be used in an unmanned situation. We use a deploying agent to drop the sensors and there is a Base Station (BS) to which the event details are communicated by connectivity through localization with neighboring sensors. The research targets dynamic deployment of sensors with coverage and connectivity handled simultaneously as the information can reach the base station only if the sensors are able to connect to it. This is critical for real time applications. So we use an intelligent distribution scheme to test the behavior of different kinds of deployments using random, Gaussian, controlled random and combinational methods to deploy sensors. The set of parameters which are constraints are the communication radius of the base station, sensors & the event, the proximity of the event from the base station and location determination of the event based on the current state of the system. We use a weighted approach with more sensors around the event border and lesser inside to be able to detect the event and yet preserve the sensors as they might be lost due to fire or damage depending on the event. Additionally partial event boundary detection is used as experiment results show that we can reduce the number of sensors by nearly 50% when 80% of the sensors deployed are connected as against 100% connectivity. Test cases also involve multiple BS & deploying agents with parallel control. This will be useful in emergency situations and specifically in situations which do not have pre-deployed sensors wherein, time and resources available are important constraints.
Dharma Agrawal, DSc (Committee Chair)
Raj Bhatnagar, PhD (Committee Member)
George Purdy, PhD (Committee Member)
127 p.
Computer Science
Dynamic network deployment strategies; realtime partial boundary detection; ad-hoc wireless sensor networks; localization; coverage connectivity detectivity; unknown event boundary detection

Recommended Citations

Citations

  • Venkataraman, A. (2011). Dynamic Deployment strategies in Ad-Hoc Sensor networks to optimize Coverage and Connectivity in Unknown Event Boundary detection [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1313773833

    APA Style (7th edition)

  • Venkataraman, Aparna. Dynamic Deployment strategies in Ad-Hoc Sensor networks to optimize Coverage and Connectivity in Unknown Event Boundary detection. 2011. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1313773833.

    MLA Style (8th edition)

  • Venkataraman, Aparna. "Dynamic Deployment strategies in Ad-Hoc Sensor networks to optimize Coverage and Connectivity in Unknown Event Boundary detection." Master's thesis, University of Cincinnati, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1313773833

    Chicago Manual of Style (17th edition)

ucin1313773833
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© 2011, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.