Research On Coverage Control In Wireless Sensor Networks

Wireless Sensor Networks (WSNs) play an important role in next generation networks. As an emerging technology with great potential to drive the development of science and technology, promote the advancement of society, and impact national politics and security, WSNs have become a primary focus of international competitors. In wireless sensor networks applications, network coverage reflects an ability of monitoring the physical world, often as a description to monitor standards of the quality of service (Quality of Service, QoS). As the application characteristic for large scale, the energy constraints, with limited computing ability and communication ability. The sensor nodes are often deployed with large-scale, high-density in monitored region, which brings conflicts between deployment costs and deployment quality, the energy constraints of nodes and network lifetime. Coverage control by modeling the sensing ability of sensor nodes, combined with application requirements, effectively obtain information in monitoring area by deployment of sensor nodes. And without sacrificing system original performance by putting some sensor nodes into active state for the sensing and communication tasks while other sensor nodes remain low-power sleep state. The network lifetime is prolonged by efficiently using a variety of resources. Finally, the QoS is improved in monitored region.In this dissertation, we mainly focus on coverage control problems in wireless sensor networks. The outline of this dissertation is described as follows:1) Two coverage-guaranteed sensor node deployment strategies for wireless sensor networks are proposed to overcome coverage overestimation problem induced by border effects. Eg. Expected-area Coverage Deployment (ECD) and BOundaryAssistant Deployment (BOAD), and then coverage quality requirements can be satisfied in real deployment. Deployment quality and cost are two conflicting aspects in wireless sensor networks. Their successful applications depend considerably on the deployment quality that uses the minimum number of sensors to achieve a desired coverage. Currently, the number of sensors required to meet the desired coverage is based on asymptotic analysis, which cannot meet deployment quality due to coverage overestimation in real applications. To overcome this problem, we propose two deployment strategies, namely, the expected-area coverage deployment strategy and boundary assistant deployment strategy. The deployment quality of the two strategies is analyzed mathematically. Under the analysis, a lower bound on the number of deployed sensor nodes is given to satisfy the desired deployment quality. We justify the correctness of our analysis through rigorous proof, and validate the effectiveness of the two strategies through extensive simulation experiments. The simulation results show that both strategies alleviate the coverage overestimation significantly. In addition, we also evaluate two proposed strategies in the context of target detection application. The comparison results demonstrate that if the target appears at the boundary of monitored region in a given random deployment, the average intrusion distance of BOAD is considerably shorter than that of ECD with the same desired deployment quality. In contrast, ECD has better performance in terms of the average intrusion distance when the invasion of intruder is from the inside of monitored region. The general monitored region and probabilistic sensing model are extended for two deployment strategies.2) A distance-assistant node coverage identification model is proposed by using distance information between the node and its neighbors to identify nodes coverage without using any location information. The coverage degree can accurately determined by the neighbor nodes. Based on this model, a NDNS (Non-uniform Distribution NodeScheduling) is proposed which satisfies with different random distribution. Aiming at the defect that high computational complexity of exact location information and the distribution limitation of location information-free in traditional schemes, the node distribution is analyzed theoretically. A distance-assistant node coverage identification model(DANCI) is proposed which adopts distance information between the node and its neighbors to identify nodes coverage without using any location information. A node scheduling scheme NDNS based on DANCI is proposed which satisfies with different random distribution. Theory analysis and simulation results are presented to evaluate the proposed DANCI model. It is shown that in randomly deployed sensor networks, the maximum coverage error is 6.396 0% between DANCI model and location information-aware strategy. The numerical experiments results illustrate that the longer network lifetime is achieved in preserving networks coverage.3) A node scheduling scheme based on tolerable coverage area is proposed. The node scheduling problem conduced by the inequality sleeping in location-free conditions is alleviated by proposed algorithm. Traditional methods of node scheduling without location information are aiming at node sensing area coverage. It leads to nodes in the border of monitored region or some nodes without neighbors in monitored region die first due to having no chance to enter sleep state, and then the death spreads to the central region. We call this phenomenon as inequality sleep problems. To address this problem, from the theoretical analysis of the sensor node coverage model, we propose the concept of tolerable coverage area, and a node scheduling scheme based on tolerable coverage area. Simulation results demonstrate that the proposed method not only alleviates the inequality sleep problems, but also prolongs network lifetime.4) An intrusion detection model is suggested, in which the intruder can be detected immediately by at least k sensor nodes under practical considerations. The problem that the sensing capabilities of sensors are affected by environmental factors in real deployment is investigated. The detection probability by at least k sensors under practical considerations is studied. Target detection and field surveillance are among the most prominent applications of wireless sensor networks. The quality of detection achieved by a sensor network can be quantified by evaluating the probability of detecting a mobile target crossing a sensing field. Detection probability of sensor nodes has been studied in sensor networks for many purposes such as quality of service and decision-making. However, the sensing capabilities of sensors are affected by environmental factors in real deployment. The problem of detecting probability in a log-normal shadow fading environment is investigated. It presents an analytic method to evaluate the detection probability by at least k sensors under practical considerations. Furthermore, we also shows that shadow fading makes significant influence in detection probability compared to unit disk sensing model through extensive simulation experiments.