Abstract
Connected coverage, which reflects how well a target field is monitored under the base station, is the most important performance metric used to measure the quality of surveillance that wireless sensor networks (WSNs) can provide. To facilitate the measurement of this metric, we propose two novel algorithms for individual sensor nodes to identify whether they are on the coverage boundary, i.e., the boundary of a coverage hole or network partition. Our algorithms are based on two novel computational geometric techniques called localized Voronoi and neighbor embracing polygons. Compared to previous work, our algorithms can be applied
to WSNs of arbitrary topologies. The algorithms are fully distributed in the sense that only the minimal position information of one-hop neighbors and a limited number of simple local computations are needed, and thus are of high scalability and energy efficiency. We show the correctness and efficiency of our algorithms by theoretical proofs and extensive simulations
Contents
1. Introduction
2. Preliminaries
2.1. Notation, assumption and network model
2.2. Formal definition of the problem
2.3. State of the art
3. Localized Voronoi Polygons
3.1. Definition and properties of LVPs
3.2. LVP-based boundary node detection
3.3. Validating the algorithm
3.4. Discussions on LVP-based detection
4. Neighbor embracing polygons
4.1. Definition and properties of NEPs
4.2. NEP-based boundary node detection
4.3. Validating the algorithm
4.4. Discussions on NEP-based detection
5. Performance evaluation
5.1. Validating the accuracy with simulation results
5.2. Cost analysis
5.3. Evaluation of energy consumption for VP- and LVP-based approaches
5.4. Simulation results
6. Conclusion
7. Appendix A: Remarks on disk sensing and communication models
8. Appendix B: Locality of boundary node detection
9. References