Efficient Sensor Deployment Control Schemes and Performance Evaluation for Obstacle and Unknown Environments

Deployment is a fundamental issue for wireless sensor networks (WSNs). A well-designed deployment control method not only directly influences the number of deployed sensors, but also influences on data accuracy and network topology. Three widely discussed deployment methods are random deployment, deterministic deployment and deployment by graphic theory. Most related works have focused on the maximal deployment area problem, but few studies have considered efficient methods to solve the k-coverage problem. Moreover, such methods have high time complexity, making them unsuitable for k-covered sensor deployment. To achieve scalable and efficient deployment, this study presents two new topology deployment methods, namely the slow-start method (SSM) and square-encircled method (SEM). The proposed deployment methods can yield k-covered scenarios with minimal overlapping areas, by three different coverage sensors. SSM and SEM are without needing to pre-analyze unknown or unsafe environments when deploying a k-coverage area. Deploying and satisfying each layer until k layers are obtained requires guaranteeing k coverage. The proposed methods have time complexities of O(n2), making them suitable for WSNs. Moreover, this study first presents nine Construct Performance Evaluation (CPE) factors to evaluate the total costs of a WSN. Finally, this study evaluates the total deployment costs through CPE factors, and analyzes their performance. The simulation results clearly indicate the efficiency and effectiveness of the proposed deployment methods.