Optimization Algorithms Of Coverage Control For Wireless Sensor Networks

Wireless sensor network (WSN), as an integrated network which can perform information sensing, gathering, processing and delivering, can connect the logic information world with the real physical world. It has been greatly changing the way of interaction between human and nature. There are wide potential applications for WSNs, such as military affairs, industry, agriculture, healthcare, disaster succoring, etc. Coverage control is one of basic issue of quality of service (QoS) on WSNs. The goal of coverage control is to sense the monitoring area or targets by distributed sensors, so WSNs can collect valid and complete target information. Coverage control determines the monitoring performance on physical world for WSNs, so it is the indispensable road to accelerate the practicability of WSNs.This thesis is primarily to design optimal coverage algorithms and protocols with characteristic of energy saving for WSNs. Based on these several aspects--coverage ratio control model, polytype target coverage, multiple coverage degree, and dynamic coverage for mobile target, it follows the design criteria of reducing network consumption to achieve the purpose of an energy-efficient network coverage optimization scheme.The major work and innovative achievements of this thesis can be divided into the following four chapters:(1) Aimed at coverage ratio control of network, we propose a probability-based coverage control model (PCCM). Considering the border effect, PCCM firstly calculates the expected coverage area of sensors under the two cases:sensors located in the monitoring area, and sensors located near the border of monitoring area. Then, it gets the total expected coverage area of the deployed sensors. According to the requirements of users for coverage ratio, it gets the number of needed sensors to be deployed under the conditional probability distribution function. PCCM reflects the relationships between network coverage ratio and the number of deployed sensors, the sensing radius of sensor, the area of monitoring region. Based on the PCCM and the random graph theory, we also propose a network connectivity probability model. The proposed model can help users to control the network coverage and connectivity ratio in deploying sensors to the monitoring area.(2) Aimed at polytype target coverage for heterogeneous WSNs, we propose a cluster-based target coverage algorithm (CTCA), modeling polytype target coverage to optimal cover set problem based on linear programming. The key idea is to construct an optimal cover set in each cluster by the residual energy and coverage capability of sensors. Then, it achieves a suboptimal cover set for the whole network. Finally, CTCA schedules the corresponding sensing modules of sensor to cover the targets with same attribute. The simulation results show that the proposed algorithm can improve the energy efficiency and prolong the network lifetime.(3) Aimed at multiple degree coverage for WSNs, we propose a Reuleaux triangle-based к-coverage algorithm (RTC) on the basis of the coverage degree judgment theorem by using the geometrical characters of Reuleaux triangle. The key idea is that using the local position information of sensors to judge the coverage degree by constructing the Reuleaux triangle on the sensing circle of sensor. The algorithm schedules the suitable sensors into active status to cover target area. The simulation results show that the proposed algorithm can effectively decrease the number of sensors in the active status satisfied the coverage degree requirements, which improves the energy efficiency of network.(4) Aimed at real-time monitoring for mobile target, we propose an adaptive mobile target dynamic coverage protocol (AMTDCP). The main idea is that first the sensors near the target construct a dynamic coverage group (DCG) based on competition mechanism to locate and real-time monitor the target. Then, we use the proposed mobile target position prediction model and sensor status scheduling mechanism to update the DCG, which can improve the dynamic coverage quality and energy efficiency greatly. Finally, the communications volume of network is decreased by an adaptive data report frequency mechanism. The simulation results show that the proposed protocol has a better performance on the metrics of the total energy consumption of network, positioning accuracy, etc.In summary, this thesis focuses on coverage control problems and proposes its solutions. Our research has academic and practical value for advancing the theory and practicability in WSNs.