In several real-life scenarios, wireless sensors may be deployed in thin strip regions, such as when deploying sensors along international borders to detect illegal intrusion, around forests to detect the spread of forest fire, around a chemical factory to detect the spread of lethal chemicals, or on both sides of a long gas pipeline to detect potential sabotage. Most existing work on coverage and connectivity are not applicable to these strip deployment regions since they often ignore the boundaries of the deployment region. Further, most existing work on coverage and connectivity for random deployments provide only asymptotic results, and do not give reliable numerical conditions for determining the density required for adequate coverage in finite regions.
This project is aimed at establishing a strong foundation for coverage and connectivity when wireless sensors are deployed in thin strip regions. To achieve this goal, this project is investigating the coverage and connectivity properties for three kinds of sensors omnidirectional sensors, directional sensors (such as lasers and cameras), and mobile sensors. The project uses rigorous mathematical analysis to derive precise numerical estimates for achieving coverage and connectivity for random deployments. It is also investigating optimal algorithms (both centralized and distributed versions) for critical network activities such as coverage/connectivity verification, coverage restoration upon sensor failures, and sleep-wakeup schedule determination for network lifetime maximization. The new techniques developed in this project for deriving precise density estimates make the coverage and connectivity results readily usable in real-life, thus bridging the gap between theory and practice. The comprehensive foundation for coverage and connectivity for thin strips being created in this project is expected to make perimeter security with wireless sensors more practical.
