Good deployment of sensors empowers the network with effective monitoring ability. Different from omnidirectional sensors, the coverage region of a directional sensor is determined by not only the sensing radius (distance), but also its sensing orientation and spread angle. Heterogeneous sensing distances and spread angles are likely to exist among directional sensors, to which we refer as heterogeneous directional sensors. In this paper, we target on a bounded monitoring area and deal with heterogeneous directional sensors equipped with locomotion and rotation facilities to enable the sensors self-deployment. Two Enhanced Deployment Algorithms, EDA-I and EDA-II, are proposed to achieve high sensing coverage ratio in the monitored field. EDA-I leverages the concept of virtual forces (for sensors movements) and virtual boundary torques (for sensors rotations), whereas EDA-II combines Voronoi diagram directed movements and boundary torques guided rotations. EDA-I computations can be centralized or distributed that differ in required energy and execution time, whereas EDA-II only allows centralized calculations. Our EDA-II outperforms EDA-I in centralized operations, while EDA-I can be adapted into a distributed deployment algorithm without requiring global information and still achieves comparably good coverage performance to its centralized version. To the best of our knowledge, this is perhaps the first work to employ movements followed by rotations for sensors self-deployment. Performance results demonstrate that our enhanced deployment mechanisms are capable of providing desirable surveillance level, while consuming moderate moving and rotating energy under reasonable execution time.

With the growing popularity of wireless mobile sensors, automated sensors deployment in a smart sensing environment has become practical and feasible. Once the deployment algorithm determines moving destinations (goals) for all sensors, however, the problem of how to schedule collision-free moving paths to reach the goals safely remains largely unaddressed in the wireless sensor networking (WSN) literature. In this paper, we propose a collision-free path planning (CFPP) mechanism, based on geometric formulations and batched movements, to address the sensors deployment problem. Our proposed CFPP mechanism ensures 100% sensors goal reachability, which is critical for most WSN monitoring applications that require sufficient sensing coverage to operate correctly. Performance results show that our CFPP outperforms other existing path-planning mechanisms in terms of computation latency, energy consumption, and sensors reachability (goals reaching success probability).