Barrier Coverage in Wireless Sensor Networks

Barrier coverage is a critical issue in wireless sensor networks (WSNs) for security applications, which aims to detect intruders attempting to penetrate protected areas. However, it is difficult to achieve desired barrier coverage after initial random deployment of sensors because their locations cannot be controlled or predicted. In this dissertation, we explore how to leverage the mobility capacity of mobile sensors to improve the quality of barrier coverage. We first study the 1-barrier coverage formation problem in heterogeneous sensor networks and explore how to efficiently use different types of mobile sensors to form a barrier with pre-deployed different types of stationary sensors. We introduce a novel directional barrier graph model and prove that the minimum cost of mobile sensors required to form a barrier with stationary sensors is the length of the shortest path from the source node to the destination node on the graph. In addition, we formulate the problem of minimizing the cost of moving mobile sensors to fill in the gaps on the shortest path as a minimum cost bipartite assignment problem and solve it in polynomial time using the Hungarian algorithm. We further study the k-barrier coverage formation problem in sensor networks. We introduce a novel weighted barrier graph model and prove that determining the minimum number of mobile sensors required to form k-barrier coverage is related with but not equal to finding k vertex-disjoint paths with the minimum total length on the WBG. With this observation, we propose an optimal algorithm and a faster greedy algorithm to find the minimum number of mobile sensors required to form k-barrier coverage. Finally, we study the barrier coverage formation problem when sensors have location errors. We derive the minimum number of mobile sensors needed to fill in a gap with a guarantee when location errors exist and propose a progressive method for mobile sensor deployment. Furthermore, we propose a fault tolerant weighted barrier graph to find the minimum number of mobile sensors needed to form barrier coverage with a guarantee. Both analytical and experimental studies demonstrated the effectiveness of our proposed algorithms

Enabling Cyber Physical Systems with Wireless Sensor Networking Technologies

[[abstract]]Over the last few years, we have witnessed a growing interest in Cyber Physical Systems (CPSs) that rely on a strong synergy between computational and physical components. CPSs are expected to have a tremendous impact on many critical sectors (such as energy, manufacturing, healthcare, transportation, aerospace, etc) of the economy. CPSs have the ability to transform the way human-to-human, human-toobject, and object-to-object interactions take place in the physical and virtual worlds. The increasing pervasiveness of Wireless Sensor Networking (WSN) technologies in many applications make them an important component of emerging CPS designs. We present some of the most important design requirements of CPS architectures. We discuss key sensor network characteristics that can be leveraged in CPS designs. In addition, we also review a few well-known CPS application domains that depend on WSNs in their design architectures and implementations. Finally, we present some of the challenges that still need to be addressed to enable seamless integration of WSN with CPS designs.[[incitationindex]]SCI[[booktype]]紙

Utilization Of A Large-Scale Wireless Sensor Network For Intrusion Detection And Border Surveillance

To control the border more effectively, countries may deploy a detection system that enables real-time surveillance of border integrity. Events such as border crossings need to be monitored in real time so that any border entries can be noted by border security forces and destinations marked for apprehension. Wireless Sensor Networks (WSNs) are promising for border security surveillance because they enable enforcement teams to monitor events in the physical environment. In this work, probabilistic models have been presented to investigate senor development schemes while considering the environmental factors that affect the sensor performance. Simulation studies have been carried out using the OPNET to verify the theoretical analysis and to find an optimal node deployment scheme that is robust and efficient by incorporating geographical coordination in the design. Measures such as adding camera and range-extended antenna to each node have been investigated to improve the system performance. A prototype WSN based surveillance system has been developed to verify the proposed approach

Reliable cost-optimal deployment of wireless sensor networks

Wireless Sensor Networks (WSNs) technology is currently considered one of the key technologies for realizing the Internet of Things (IoT). Many of the important WSNs applications are critical in nature such that the failure of the WSN to carry out its required tasks can have serious detrimental effects. Consequently, guaranteeing that the WSN functions satisfactorily during its intended mission time, i.e. the WSN is reliable, is one of the fundamental requirements of the network deployment strategy. Achieving this requirement at a minimum deployment cost is particularly important for critical applications in which deployed SNs are equipped with expensive hardware. However, WSN reliability, defined in the traditional sense, especially in conjunction with minimizing the deployment cost, has not been considered as a deployment requirement in existing WSN deployment algorithms to the best of our knowledge. Addressing this major limitation is the central focus of this dissertation. We define the reliable cost-optimal WSN deployment as the one that has minimum deployment cost with a reliability level that meets or exceeds a minimum level specified by the targeted application. We coin the problem of finding such deployments, for a given set of application-specific parameters, the Minimum-Cost Reliability-Constrained Sensor Node Deployment Problem (MCRC-SDP). To accomplish the aim of the dissertation, we propose a novel WSN reliability metric which adopts a more accurate SN model than the model used in the existing metrics. The proposed reliability metric is used to formulate the MCRC-SDP as a constrained combinatorial optimization problem which we prove to be NP-Complete. Two heuristic WSN deployment optimization algorithms are then developed to find high quality solutions for the MCRC-SDP. Finally, we investigate the practical realization of the techniques that we developed as solutions of the MCRC-SDP. For this purpose, we discuss why existing WSN Topology Control Protocols (TCPs) are not suitable for managing such reliable cost-optimal deployments. Accordingly, we propose a practical TCP that is suitable for managing the sleep/active cycles of the redundant SNs in such deployments. Experimental results suggest that the proposed TCP\u27s overhead and network Time To Repair (TTR) are relatively low which demonstrates the applicability of our proposed deployment solution in practice

Automatic triangulation positioning system for wide area coverage from a fixed sensors network

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonIn a wide area that many Transmitters (TRs) operate, systems of Fixed Sensors (FS) might be used in order to detect them and find TRs position. The detection and the accurate location of a new TR entering in the area frequently can be missed if the system fails to triangulate accurately the relative readings and analyze the changes in the received data. Additionally, there are cases that a Triangulation Station Network (TSN) can detect the heading as well as the transmitter’s position wrong. This thesis presents the design of a Sensors Network (FSN) system which is able to interact with a user, and exploit the relative data of the Sensors (SRs) in real time. The system performs localization with triangulation and the SRs are detect only TRs bearing data (range free). System design and algorithms are also explained. Efficient algorithms were elaborated and the outcomes of their implementation were calculated. The system design targets to reduce system errors and increase the accuracy and the speed of detection. Synchronously and through interaction with the user and changes of relative settings and parameters will be able to offer the user accurate results on localization of TRs in the area minimizing false readings and False Triangulations (FTRNs). The system also enables the user to apply optimization techniques in order to increase the system detection rate and performance and keep the surveillance in the Field of Interest (FoI) on a high level. The optimization methodology applied for the system proves that the FSN system is able to operate with a high performance even when saturation phenomena appear. The unique outcome of the research conducted, is that this thesis paves the way to enhance the localization via Triangulation for a network of Fixed Sensors with known position. The value of this thesis is that the FSN system performs bearing only detection (Range free) with a certain accuracy and the Area of Interest (AOI) is covered efficiently

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network

Barrier coverage has been widely used to detect intrusions in wireless sensor networks (WSNs). It can fulfill the monitoring task while extending the lifetime of the network. Though barrier coverage in WSNs has been intensively studied in recent years, previous research failed to consider the problem of intrusion in transversal directions. If an intruder knows the deployment configuration of sensor nodes, then there is a high probability that it may traverse the whole target region from particular directions, without being detected. In this paper, we introduce the concept of crossed barrier coverage that can overcome this defect. We prove that the problem of finding the maximum number of crossed barriers is NP-hard and integer linear programming (ILP) is used to formulate the optimization problem. The branch-and-bound algorithm is adopted to determine the maximum number of crossed barriers. In addition, we also propose a multi-round shortest path algorithm (MSPA) to solve the optimization problem, which works heuristically to guarantee efficiency while maintaining near-optimal solutions. Several conventional algorithms for finding the maximum number of disjoint strong barriers are also modified to solve the crossed barrier problem and for the purpose of comparison. Extensive simulation studies demonstrate the effectiveness of MSPA

A wireless sensor network system for border security and crossing detection

The protection of long stretches of countries’ borders has posed a number of challenges. Effective and continuous monitoring of a border requires the implementation of multi-surveillance technologies, such as Wireless Sensor Networks (WSN), that work as an integrated unit to meet the desired goals. The research presented in this thesis investigates the application of topologically Linear WSN (LWSNs) to international border monitoring and surveillance. The main research questions studied here are: What is the best form of node deployment and hierarchy? What is the minimum number of sensor nodes to achieve k− barrier coverage in a given belt region? iven an appropriate network density, how do we determine if a region is indeed k−barrier covered? What are the factors that affect barrier coverage? How to organise nodes into logical segments to perform in-network processing of data? How to transfer information from the networks to the end users while maintaining critical QoS measures such as timeliness and accuracy. To address these questions, we propose an architecture that specifies a mechanism to assign nodes to various network levels depending on their location. These levels are used by a cross-layer communication protocol to achieve data delivery at the lowest possible cost and minimal delivery delay. Building on this levelled architecture, we study the formation of weak and strong barriers and how they determine border crossing detection probability. We propose new method to calculate the required node density to provide higher intruder detection rate. Then, we study the effect of people movement models on the border crossing detection probability. At the data link layer, new energy balancing along with shifted MAC protocol are introduced to further increase the network lifetime and delivery speed. In addition, at network layer, a routing protocol called Level Division raph (LD ) is developed. LD utilises a complex link cost measurement to insure best QoS data delivery to the sink node at the lowest possible cost. The proposed system has the ability to work independently or cooperatively with other monitoring technologies, such as drowns and mobile monitoring stations. The performance of the proposed work is extensively evaluated analytically and in simulation using real-life conditions and parameters. The simulation results show significant performance gains when comparing LD to its best rivals in the literature Dynamic Source Routing. Compared to DSR, LD achieves higher performance in terms of average end-to-end delays by up to 95%, packet delivery ratio by up to 20%, and throughput by up to 60%, while maintaining similar performance in terms of normalised routing load and energy consumption

Performance optimization of wireless sensor networks for remote monitoring

Wireless sensor networks (WSNs) have gained worldwide attention in recent years because of their great potential for a variety of applications such as hazardous environment exploration, military surveillance, habitat monitoring, seismic sensing, and so on. In this thesis we study the use of WSNs for remote monitoring, where a wireless sensor network is deployed in a remote region for sensing phenomena of interest while its data monitoring center is located in a metropolitan area that is geographically distant from the monitored region. This application scenario poses great challenges since such kind of monitoring is typically large scale and expected to be operational for a prolonged period without human involvement. Also, the long distance between the monitored region and the data monitoring center requires that the sensed data must be transferred by the employment of a third-party communication service, which incurs service costs. Existing methodologies for performance optimization of WSNs base on that both the sensor network and its data monitoring center are co-located, and therefore are no longer applicable to the remote monitoring scenario. Thus, developing new techniques and approaches for severely resource-constrained WSNs is desperately needed to maintain sustainable, unattended remote monitoring with low cost. Specifically, this thesis addresses the key issues and tackles problems in the deployment of WSNs for remote monitoring from the following aspects. To maximize the lifetime of large-scale monitoring, we deal with the energy consumption imbalance issue by exploring multiple sinks. We develop scalable algorithms which determine the optimal number of sinks needed and their locations, thereby dynamically identifying the energy bottlenecks and balancing the data relay workload throughout the network. We conduct experiments and the experimental results demonstrate that the proposed algorithms significantly prolong the network lifetime. To eliminate imbalance of energy consumption among sensor nodes, a complementary strategy is to introduce a mobile sink for data gathering. However, the limited communication time between the mobile sink and nodes results in that only part of sensed data will be collected and the rest will be lost, for which we propose the concept of monitoring quality with the exploration of sensed data correlation among nodes. We devise a heuristic for monitoring quality maximization, which schedules the sink to collect data from selected nodes, and uses the collected data to recover the missing ones. We study the performance of the proposed heuristic and validate its effectiveness in improving the monitoring quality. To strive for the fine trade-off between two performance metrics: throughput and cost, we investigate novel problems of minimizing cost with guaranteed throughput, and maximizing throughput with minimal cost. We develop approximation algorithms which find reliable data routing in the WSN and strategically balance workload on the sinks. We prove that the delivered solutions are fractional of the optimum. We finally conclude our work and discuss potential research topics which derive from the studies of this thesis

A survey on gas leakage source detection and boundary tracking with wireless sensor networks

Gas leakage source detection and boundary tracking of continuous objects have received a significant research attention in the academic as well as the industries due to the loss and damage caused by toxic gas leakage in large-scale petrochemical plants. With the advance and rapid adoption of wireless sensor networks (WSNs) in the last decades, source localization and boundary estimation have became the priority of research works. In addition, an accurate boundary estimation is a critical issue due to the fast movement, changing shape, and invisibility of the gas leakage compared with the other single object detections. We present various gas diffusion models used in the literature that offer the effective computational approaches to measure the gas concentrations in the large area. In this paper, we compare the continuous object localization and boundary detection schemes with respect to complexity, energy consumption, and estimation accuracy. Moreover, this paper presents the research directions for existing and future gas leakage source localization and boundary estimation schemes with WSNs