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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Optimization of self-directed target coverage in wireless multimedia sensor network.

Yang Yang1, Yufei Wang2, Dechang Pi3

  • 1College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China ; Department of Information Technology, Nanjing Radio and TV University, Nanjing City Vocational College, Nanjing, Jiangsu 210002, China.

Thescientificworldjournal
|August 20, 2014
PubMed
Summary
This summary is machine-generated.

New algorithms optimize target coverage in wireless multimedia sensor networks (WMSNs) using a field of view (FoV) model. This approach efficiently determines sensor orientation for effective target detection, even in complex scenarios.

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Wireless Sensor Networks

Background:

  • Traditional sensor network coverage methods are inadequate for wireless multimedia sensor networks (WMSNs) due to sensor limitations.
  • WMSNs utilize video/image sensors with directed views and limited sensing angles, necessitating new coverage models.
  • Existing circular sensing models do not account for the directional nature of WMSN sensors.

Purpose of the Study:

  • To propose novel field of view (FoV) sensing and FoV disk models for WMSNs.
  • To develop target coverage optimization algorithms tailored for WMSN sensor characteristics.
  • To address single-sensor/single-target, multi-sensor/single-target, and single-sensor/multi-target coverage problems.

Main Methods:

  • Defined expected sensor coverage based on deflection angle and distance using proposed FoV models.
  • Developed distinct algorithms for various coverage scenarios (single-sensor/single-target, multi-sensor/single-target, single-sensor/multi-target).
  • Employed a genetic algorithm to solve the NP-complete multi-sensor/multi-target coverage problem for optimal sensor subset selection.

Main Results:

  • Algorithms effectively optimize target coverage by selecting sensor orientations based on expected coverage values.
  • The genetic algorithm provides an approximated minimum subset of sensors for comprehensive network coverage.
  • Simulation results validate the algorithm's performance and analyze the impact of target density on coverage.

Conclusions:

  • The proposed FoV models and optimization algorithms are suitable for WMSN target coverage.
  • The study presents an efficient approach to minimize sensor subsets while maximizing target coverage.
  • This research contributes to improving the efficiency and effectiveness of WMSNs in multimedia applications.