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Rechargeable Sensor Networks. Ilhan Akbas and Volodymyr Prymma University of Central Florida Orlando, FL. Overview. Introduction Rechargeable Sensor Network Testing Scenarios Simulation Results Demonstration Conclusion. Introduction. Miniaturization Smaller sensors
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Rechargeable Sensor Networks Ilhan Akbas and Volodymyr Prymma University of Central Florida Orlando, FL
Overview • Introduction • Rechargeable Sensor Network • Testing Scenarios • Simulation Results • Demonstration • Conclusion
Introduction • Miniaturization • Smaller sensors • Lower energy consumption • Micro-sensors • Very small devices • Limited functionality/resources • Rechargeable
Introduction • Applications • Various military operations • Natural disaster monitoring/recovery • Rescue operations • Simple environment monitoring • Need for autonomous architecture
Introduction • ANSWER • AutoNomouS netWorked sEnsoR system • Developed by Dr. Olariou et al. • Self-organizing architecture • Our contribution • Addition of rechargeable sensors • Performance evaluation rechargeable vs. non-rechargeable
Rechargeable Sensor Network • ANSWER Architecture • Large number of micro-sensors • A number of AFNs • Single mobile node • Unique coordinate system
Rechargeable Sensor Network • Dynamic coordinate system • Concentric coronas • Centered at training agent (TA) • Equiangular wedges • Self-organization • Easy clustering
Rechargeable Sensor Network Dynamic coordinate system
Rechargeable Sensor Network Communication schemes
Rechargeable Sensor Network • Coloring scheme • Coronas are further subdivided • Each node has a specific color • Colors are assigned based on signal strength • Allows for activation of nodes in subsets
Rechargeable Sensor Network Coloring scheme
Rechargeable Sensor Network Micro-sensor states
Testing Scenarios • Scenario 1 • One stationary threat node • Positioned directly in the path of mobile node • 200 micro-sensor nodes • 6 AFNs • Mobile node • Move from top left corner to bottom right
Testing Scenarios • Scenario 2 • Ten stationary threat nodes • Positioned randomly in the vicinity of the network • 200 micro-sensor nodes • 6 AFNs • Mobile node • Move from top left corner to bottom right
Testing Scenarios • Scenario 3 • One mobile threat node • Set to move from top right corner to bottom left • Intersects the path of mobile node • 200 micro-sensor nodes • 6 AFNs • Mobile node • Move from top left corner to bottom right
Testing Scenarios • Scenario 4 • Ten mobile threat nodes • Set to move randomly • 200 micro-sensor nodes • 6 AFNs • Mobile node • Move from top left corner to bottom right
Simulation Results • Metrics • Avg. failures vs. number of nodes • Avg. failures vs. mobility • Avg. energy consumption vs. number of nodes • Avg. energy consumption vs. mobility • Comparisons • Rechargeable vs. non-rechargeable nodes
Simulation Results Avg. failures vs. number of nodes
Simulation Results Avg. failures vs. mobility
Simulation Results Avg. energy consumption vs. number of nodes
Simulation Results Avg. energy consumption vs. mobility
Demonstration YAES Screenshot
Conclusion • ANSWER • Provides reliable architecture • Better results with dense network • All scenarios had similar results • Rechargeable vs. Non-Rechargeable • Rechargeable implementation has better performance • Fewer failures • Less energy consumption