K-barrier Coverage Research Articles

An efficient exact method with polynomial time-complexity to achieve [formula omitted]-strong barrier coverage in heterogeneous wireless multimedia sensor networks

Barrier coverage in Wireless Sensor Networks (WSNs) plays a pivotal role in surveillance and security applications. It serves as a fundamental mechanism for identifying and detecting potential intruders who endeavor to infiltrate a sensor barrier. Achieving k-strong barrier coverage is a vital indicator of a WSN’s capability to detect unauthorized intrusions. This paper establishes efficient k-strong barrier coverage in hybrid wireless multimedia sensor networks, referred to as MMS-KSB. The primary goal is to identify a minimal number of mobile sensors to obtain k-barrier coverage. Exhibiting the combinatorial structure, previous research on building k-strong barrier has failed to provide a polynomial time solution for the considered problem and resorted to approximation algorithms. We, therefore, introduce a precise algorithm, named ExA-KSB, and provide theoretical analysis to substantiate that our proposed method achieves an exact solution with polynomial time complexity. Furthermore, we conduct comprehensive experiments to evaluate the efficacy of our algorithm by comparing it with existing approaches. Numerical results demonstrate that ExA-KSB surpasses previous algorithms, and offers superior solution quality with competitive computational efficiency.

A Gaussian process regression approach to predict the k-barrier coverage probability for intrusion detection in wireless sensor networks

Sensors in a Wireless Sensor Network (WSN) sense, process, and transmit information simultaneously. They mainly find applications in agriculture monitoring, environment monitoring, smart city development and defence. These applications demand high-end performance from the WSN. However, the performance of a WSN is highly vulnerable to various types of security threats. Any intrusion may reduce the performance of the WSN and result in fatal problems. Hence, fast intrusion detection and prevention is of great use. This paper aims towards fast detection and prevention of any intrusion using a machine learning approach based on Gaussian Process Regression (GPR) model. We have proposed three methods (S-GPR, C-GPR and GPR) based on feature scaling for accurate prediction of k-barrier coverage probability. We have selected the number of nodes, sensing range, Sensor to Intruder Velocity Ratio (SIVR), Mobile to Static Node Ratio (MSNR), angle of the intrusion path, and required k as the potential features. These features are extracted using an analytical approach. Simulation results demonstrate that the proposed method III accurately predicts the k-barrier coverage probability and outperforms the other two methods (I and II) with a correlation coefficient (R = 0.85) and Root Mean Square Error (RMSE = 0.095). Further, the proposed methods achieve a higher accuracy as compared to other benchmark schemes.

On guarding real terrains: The terrain guarding and the blocking path problems

Locating a minimum number of guards on a terrain such that every point on the terrain is guarded by at least one of the guards is known as the Terrain Guarding Problem (TGP). In this paper, a realistic example of the terrain guarding problem is studied, involving the surveillance of a rugged geographical terrain by means of thermal cameras. A number of issues related to TGP are addressed with integer-programming models proposed to solve the problem. Also, a sensitivity analysis is carried out in which five fictitious terrains are created to see the effect of the resolution of the terrain, and of terrain characteristics, on coverage optimization and the required number of guards. Finally, a new problem, which is called the Blocking Path Problem (BPP), is introduced. BPP is about guarding a path on the terrain with a minimum number of guards such that the path blocks all possible infiltration routes. A discussion is provided about the relation of BPP to the Network Interdiction Problem (NIP), which has been studied extensively by the operations research community, and to the k-Barrier Coverage Problem, which has been studied under the Sensor Deployment Problem. BPP is solved via an integer-programming formulation based on a network paradigm.

Energy-efficient non-linear k-barrier coverage in mobile sensor network

K-barrier coverage is an important coverage model for achieving robust barrier coverage in wireless sensor networks. After initial random sensor deployment, k-barrier coverage can be achieved by moving mobile sensors to form k barriers consisting of k sensor chains crossing the region. In mobile sensor network, it is challenging to reduce the moving distances of mobile sensors to prolong the network lifetime. Existing work mostly focused on forming linear barriers, that is the final positions of sensors are on a straight line, which resulted in large redundant movements. However, the moving cost of sensors can be further reduced if nonlinear barriers are allowed, which means that sensors? final positions need not be on a straight line. In this paper, we propose two algorithms of forming non-linear k barriers energy-efficiently. The algorithms use a novel model, called horizontal virtual force model, which considers both the euclidean distance and horizontal angle between two sensors. Then we propose two barrier forming algorithms. To construct a barrier, one algorithm always chooses the mobile sensor chain with the largest horizontal virtual force and then flattens it, called sensor chain algorithm. The other chooses the mobile sensor with the largest horizontal virtual force to construct the barrier, other than the mobile sensor chain, called single sensor algorithm. Simulation results show that the algorithms significantly reduce the movements of mobile sensors compared to a linear k-barrier coverage algorithm. Besides, the sensor chain algorithm outperforms the single sensor algorithm when the sensor density becomes higher.

K-barrier coverage reliability evaluation for wireless sensor networks using two-dimensional k-within-consecutive-r × s-out-of-m × n:F system

The reliability of k-barrier coverage for wireless sensor networks is evaluated in this article. We construct a two-dimensional k-within-consecutive- r × s-out-of- m × n:F system to describe the k-barrier coverage problem and propose the definition of the k-barrier coverage reliability. If the sensing radius r of each sensor is equal to half of the horizontal distance d between two adjacent sensors, then the formula for calculating the k-barrier coverage reliability can be derived directly. If r is a positive integer multiple of d, then a recursive algorithm is applied to calculate the coverage reliability. The effects of the probability that sensors are active, the number of rows of deployed sensors and the number of sensors in each row on the coverage reliability are also analyzed using some illustrative examples. The results show that, if r = d/2, the reliability of a barrier decreases with an increase in the length of the barrier; if r = t × d ( t is a positive integer), the reliability of a barrier hardly decreases with an increase in the length of the barrier.

Hierarchy Graph Based Barrier Coverage Strategy with a Minimum Number of Sensors for Underwater Sensor Networks.

Underwater sensor networks based barrier coverage is increasingly important for intrusion detection due to the scarcity of underwater sensor resource. To improve UWSNs’ detection performance and prolong their lifetime, an efficient barrier coverage strategy is very important. In this paper, a novel concept: hierarchy graph is proposed. Hierarchy graph can make the network’s topology more clarity. In accordance with the hierarchy graph, 1-barrier coverage algorithm and k-barrier coverage algorithm are presented to construct the barrier with less sensors for higher energy efficiency. Both analytical and simulation studies demonstrate that the proposed algorithms can provide high detection probability and long lifetime for UWSNs.

Weak k-Barrier Coverage Problem in Underwater Wireless Sensor Networks

Most existing works on barrier coverage assume that sensors are deployed in a two-dimensional (2D) long thin belt region, where a barrier is a chain of sensors from one end of the region to the other end with overlapping sensing zones of adjacent sensors. However, the 2D assumption cannot cover all application scenarios, e.g., underwater wireless sensor networks, where sensors are finally distributed over three-dimensional (3D) underwater environment. In this paper, we investigate weak k-barrier coverage problem in underwater wireless sensor networks. We first analyse how to determine whether a deployed underwater wireless sensor network provides 3D weak k-barrier coverage, and propose a novel and effective scheme to transform the 3D weak k-barrier coverage problem into 2D complete k-coverage problem, based on which we devise an O(n2) time algorithm for the 3D weak k-barrier decision problem. Furthermore, we propose a parallel movement manner, based on which an effective algorithm called Hungarian Method-based sensor assignment algorithm (HMB-SAA) is proposed for constructing weak k-barrier coverage while minimizing the total movement distance of all sensors in underwater wireless sensor networks. Simulation results validate the correctness of our analysis, and show that the proposed algorithm outperforms the GreedyMatch algorithm. To the best of our knowledge, this is the first result for 3D weak k-barrier coverage problem in underwater wireless sensor networks.

Scheduling algorithms for K-barrier coverage to improve transmission efficiency in WSNs

K-barrier coverage optimization problem is concentrating on how to select sensor nodes from the monitoring area of the wireless sensor networks (WSNs) to form the highest quality of k-barrier coverage. Sink-connected barrier coverage optimization problem (SCBCOP) focuses on how to choose the minimum number of forwarding nodes to make each detecting node sink-connected for the security requirements of the belt monitoring region. However, the existing algorithm, such as optimal node selection algorithm(ONSA), can find the optimized k-barrier coverage of sink-connected, but it may form a large number of data packets interference (or collisions) and cannot transfer the information to sink nodes in time because the different detecting nodes can transmit invasive information at the same time. The purpose of this paper is to discuss how to reduce interference among the nodes and select routing path to optimize k-barrier coverage and satisfy sink-connected. In this paper a scheduling algorithm is proposed to build the routing path and maintain sink-connected. The algorithms is present in detail through forwarding routing tree and multi-channel scheduling to further reduce the interference of packet transmission among sensor nodes. Moreover, the comparison between other approaches and our proposal is mentioned through the simulation to show the potential efficiency and better performance of interference of packet transmission among sensor nodes with the lower packet loss rate, the shorter packet delay and the larger network average throughput.

Investigating physical security in stealthy lattice wireless sensor networks using k-barrier coverage

Any unauthorized access to a critical space is a physical breach in our society that can be viewed as a physical security problem. It is essential to build a barrier that prevents any intruder's attempt to cross it and access a critical area. In this paper, we address the problem of physical security in stealthy lattice wireless sensor networks using a belt of sensors around a critical area. Precisely, we propose a theoretical framework to analyze the k-barrier coverage problem, where any path that crosses this belt intersects with the sensing range of at least k sensors, k ≥ 1. Precisely, we analyze the k-barrier coverage problem from a tiling perspective, where the sensors’ sensing disks are tangential to each other. We study two deterministic sensor deployment strategies, which yield square lattice and hexagonal lattice wireless sensor networks, respectively. First, we introduce the concept of intruder's abstract paths along a k-barrier covered sensor belt region, and compute their number. Second, we propose a polynomial representation of all abstract paths. Third, we compute the number of sensors deployed over a k-barrier covered sensor belt region for both lattices. Fourth, we define the concept of weakly k-barrier covered path crossing a k-barrier covered sensor belt region, and compute its length for both lattices. Also, we define the observability of intruder's abstract path, and compute its value for both lattices. Fifth, we generalize our results for random intruder's moves across a k-barrier covered sensor belt region. Sixth, we corroborate our analysis with simulation results.

Implementation and Analysis of k-Barrier Coverage in Wireless Sensor Networks

Implementation and Analysis of k-Barrier Coverage in Wireless Sensor Networks

QoS guaranteed surveillance algorithms for directional wireless sensor networks

A directional wireless sensor network (DWSN) consists of a number of directional sensors. Many types of directional sensors have been widely used in constructing a wireless sensor network for IoT applications. These types of sensors include infrared sensors, microwave sensors, ultrasonic sensors, cameras, and radar. Compared with an omni-directional sensor, a directional sensor can achieve better performance because it can additionally report the direction of an intruder. Unfortunately, most existing barrier-coverage mechanisms adopt omni-directional sensor networks. They cannot be efficiently applied to DWSNs because the sensing area of each directional sensor is fan-shaped. This paper investigates the surveillance service problem which supports the surveillance quality of k-barrier coverage in DWSNs. Three algorithms, called BA, BTA and BRA, are proposed which aim at finding a maximal number of different defense barriers, each of which supports k-coverage. Using these algorithms, at least k directional sensors can detect intruders intending to cross the monitoring area. Performance analyses of the proposed algorithms are conducted in Section 5 to verify the performance improvement from a theoretical point of view. In the performance study, the proposed algorithms are compared with other existing algorithms. The experimental study shows that the proposed k-barrier coverage algorithm achieves similar performance with the optimal solution but has fewer control packets. Furthermore, the proposed BRA achieves better performance in terms of the numbers of control packets and constructed defense barriers, as compared with existing algorithms.

K-barrier coverage in wireless sensor networks based on immune particle swarm optimisation

Barrier coverage of wireless sensor networks (WSNs) has been an interesting research issue for security applications. In order to increase the robustness of barriers coverage, k-barrier coverage is proposed to address this issue. In this paper, the k-barrier coverage problem is formulated as a global optimisation problem solved by particle swarm optimisation (PSO). However, the performance of PSO greatly depends on its parameters and it often suffers from being trapped in local optima. A novel particle swarm optimisation program named AI-PSO (artificial immune-particle swarm optimisation) is designed and the model of k-barrier coverage problem is proposed to solve this problem. AI-PSO integrates the ability to exploit in PSO with the ability diversity maintenance mechanism of AI (artificial immune) to synthesise both algorithms' strength. Simulation results show that the proposed algorithm is effective for the k-barrier coverage problems.

K-barrier coverage in wireless sensor networks based on immune particle swarm optimisation

K-barrier coverage in wireless sensor networks based on immune particle swarm optimisation

On-Supporting Energy Balanced $k$ -Barrier Coverage in Wireless Sensor Networks

Barrier coverage in the area of wireless sensor networks (WSNs) has received much attention in the past few years. To guarantee the competent monitoring quality of intruder detection, it is necessary that the barrier satisfies the k-barrier coverage. However, the efficient construction of the k-barrier whilst maximizing the network lifetime of a given WSN remains an issue. In this paper, an Efficient k-Barrier Construction Mechanism (EBCM) is proposed. Three phases are presented in EBCM. First, the Cover Adjacent Net (CA-Net) phase is developed, aiming to simplify the k-barrier coverage problem while reducing the complexity of computation. Second, based on the CA-Net, the construction of defense k-barrier phase is further introduced, aiming to construct a maximum number of distinct k-barriers. Each of the barriers is composed of a minimum number of sensors. Finally, a Barrier Energy Scheduling is proposed, aiming to schedule the sleep-wake time of all the constructed barriers for achieving its energy balance purpose. Simulation results show the effectiveness of the proposed mechanisms in terms of control overhead, number of barrier constructed and sensors required, sensor utilization, efficiency and success ratio of barrier construction, and network lifetime.

Minimum Perimeter Coverage Set Based on Points of Tangency and Strong Barrier for an Extended WSN Lifetime

The random deployment of sensors in the area of interest triggers several research issues. Among them, we can cite connectivity, localization and coverage. In this paper, we focus on the latter one. Our objective is to monitor the perimeter of a region of interest with circular shape from intrusions. We propose a new approach to define the minimum coverage set based on points of tangency and strong barrier coverage. Furthermore, in order to exploit the redundancy of information due to the random deployment of nodes, we also suggest a new approach to generate the scheduling sets, which consists on the creation of multiple virtual perimeters around the area of interest, upon which the minimum coverage sets is constructed. In other words, the objective is to minimize the number of nodes in coverage set and to maximize the number of coverage sets for scheduling. These disjoint sets of sensors can be activated one after the other to further extend the network lifetime or multiple sets at time and reach k-barrier coverage for strong surveillance applications. Simulation results show that to generate the minimum coverage set, our approach gives better results compared to those proposed in the literature. Moreover, the approach of constructing the scheduling sets significantly increases the network lifetime.

Solving k-Barrier Coverage Problem Using Modified Gravitational Search Algorithm

Coverage problem is a critical issue in wireless sensor networks for security applications. The k-barrier coverage is an effective measure to ensure robustness. In this paper, we formulate the k-barrier coverage problem as a constrained optimization problem and introduce the energy constraint of sensor node to prolong the lifetime of the k-barrier coverage. A novel hybrid particle swarm optimization and gravitational search algorithm (PGSA) is proposed to solve this problem. The proposed PGSA adopts a k-barrier coverage generation strategy based on probability and integrates the exploitation ability in particle swarm optimization to update the velocity and enhance the global search capability and introduce the boundary mutation strategy of an agent to increase the population diversity and search accuracy. Extensive simulations are conducted to demonstrate the effectiveness of our proposed algorithm.

Barrier coverage in energy harvesting sensor networks

Wireless Sensor Networks (WSNs) can be used effectively to form barriers that monitor strips of land for applications such as homeland security and critical infrastructure protection. When WSNs are used as barriers, they are typically deployed for extended period of time, so it is of great importance that the network has a long lifetime. Sensors are highly constrained in their energy usage, even when deploying the current energy-harvesting technology. It is necessary that the harvested energy be used effectively. The lifetime problem for WSNs with no energy harvesting has been studied extensively. In this paper, we study lifetime issues of the k-barrier coverage problem for energy harvesting WSNs. First we develop an algorithm that finds a repeating sleep/wakeup schedule that can provide the perpetual operation of the maximum number of barriers in an energy harvesting WSN. Then in the case that perpetual operation can not be achieved, we give an exact solution to the problem of achieving maximum lifetime for the application of k-barrier coverage in energy harvesting WSNs.

MobiBar: An autonomous deployment algorithm for barrier coverage with mobile sensors

Critical homeland security applications, such as international border surveillance and zone monitoring in case of biological attacks, require the timely creation of a barrier of sensors along the border to be monitored. Mobile Wireless Sensor Networks have the potential to meet the desired coverage requirements, by exploiting the device coordination and self-deployment capabilities. However the design of effective and efficient algorithms is challenging. In this paper we propose MobiBar, an autonomous deployment algorithm for k-barrier coverage with mobile sensors. MobiBar coordinates sensor movements in order to construct k distinct complete barriers and to ensure the desired level of redundancy. We formally prove that MobiBar terminates in a finite time and that the final deployment provides the maximum level of barrier coverage with the available sensors. Furthermore, we show that MobiBar is able to self-reconfigure and self-heal the network to deal with dynamic coverage requirements and sudden sensor failures. We study the performance of MobiBar by means of simulations. Results show that it achieves performance close to centralized solutions and it outperforms recent distributed approaches with respect to several performance metrics.

Efficient algorithm for k-barrier coverage based on integer linear programming

Barrier coverage of wireless sensor networks is an important issue in the detection of intruders who are attempting to cross a region of interest. However, in certain applications, barrier coverage cannot be satisfied after random deployment. In this paper, we study how mobile sensors can be efficiently relocated to achieve k-barrier coverage. In particular, two problems are studied: relocation of sensors with minimum number of mobile sensors and formation of k-barrier coverage with minimum energy cost. These two problems were formulated as 0–1 integer linear programming (ILP). The formulation is computationally intractable because of integrality and complicated constraints. Therefore, we relax the integrality and complicated constraints of the formulation and construct a special model known as RELAX-RSMN with a totally unimodular constraint coefficient matrix to solve the relaxed 0–1 ILP rapidly through linear programming. Theoretical analysis and simulation were performed to verify the effectiveness of our approach.

Strong k-Barrier Coverage for One-Way Intruders Detection in Wireless Sensor Networks

Intruders detection is one of the very important applications in Wireless Sensor Networks (WSNs). Sometimes detecting intruders is not sufficient; distinguishing whether an intruder is legal or illegal is necessary. Since k-barrier coverage is widely used in detecting intruders, a barrier construction algorithm is needed, which can not only detect an intruder but also judge an illegal intruder. An intruder is defined as illegal if and only if it crosses straightly through the monitored region from the special side to another side. On the contrary, it is a legal intruder. To detect an intruder and distinguish whether the intruder is legal or illegal, a strong k-barrier coverage algorithm is proposed. The strong k-barrier coverage is a local barrier constructing algorithm and can detect any intruder crossing the k-barrier with a full probability. The strong k-barrier coverage detects all intruders penetrating the annular region for k times. What is more, the proposed strong k-barrier algorithm can provide a reliable judgement on whether an intruder is legal or illegal, and the constructed k-barrier coverage is different from the traditional one-way barrier coverage using binary barriers that are intersected but not overlapped. Some simulation tests show that the proposed algorithm can construct strong k-barrier coverage very well.