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Published on: September 7, 2018
Critical behavior of blind spots in sensor networks
Liang Huang1, Ying-Cheng Lai, Kwangho Park
1Department of Electrical Engineering, Arizona State University, Tempe, Arizona 85287, USA.
Chaos (Woodbury, N.Y.)
|July 7, 2007
Summary
This study analyzes blind spots in sensor networks caused by node power cycles. We developed formulas to predict blind spot probability and critical points across various network topologies, aiding network resilience.
Area of Science:
- Network Science
- Information Theory
- Complex Systems
Background:
- Blind spots in sensor networks, where nodes become isolated, are a significant concern for data collection and processing.
- The on-and-off cycling of sensor nodes due to power limitations can create these critical blind spots.
Purpose of the Study:
- To investigate the dynamics and critical behavior of blind spots in sensor networks.
- To understand how network topology and node occupying probability influence the occurrence of blind spots.
Main Methods:
- Developed theoretical formulas to relate blind spot probability to occupying probability for regular, random, and mixed networks.
- Proposed a procedure to estimate the critical point for blind spot occurrence in scale-free networks.
- Utilized theoretical and numerical analyses to study network partitioning dynamics.
Main Results:
- Provided theoretical formulas for calculating blind spot probability and critical points in various network types.
- Established a method for estimating critical points in scale-free networks.
- Demonstrated the dependence of blind spot dynamics on network topology and node occupying probability.
Conclusions:
- The study offers a theoretical framework for understanding and predicting blind spots in sensor networks.
- Findings are applicable to diverse network types beyond sensor networks, including wireless cellular and transportation networks.
- The research provides insights into managing network partitioning issues and enhancing overall network robustness.
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