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.

Enhancing Resolution and Fault Tolerance of Barrier Coverage with Unmanned Aerial Vehicles

Securing the borders of a protected region using sensor network deployment is termed “barrier coverage.” Unmanned aerial vehicles (UAVs) with cameras pointed downward can serve as mobile sensors to achieve barrier coverage of a protected region. The resolution of the camera, in addition to the extent of coverage, is a crucial parameter used to evaluate the quality of barrier coverage of a region. This paper presents a cost function that measures the resolution of a barrier coverage network, which can be used to improve the quality of an already established barrier-covered network. An optimization problem is proposed to find the barrier coverage while adhering to an overlapping constraint for UAVs that are placed arbitrarily in the belt. The approach is also demonstrated to be applicable for borders of any shape by utilizing multiple rectangular belts in combination. Furthermore, a fault tolerance model is proposed to ensure continuous barrier coverage even in the presence of faulty UAVs. This model utilizes nearby functional UAVs to compensate for any gaps and preserve the overlap constraint. Specifically, the model identifies neighboring functional UAVs for each faulty UAV and uses them to maintain barrier coverage.

Microglial roles in Alzheimer's disease: An agent-based model to elucidate microglial spatiotemporal response to beta-amyloid.

Alzheimer's disease (AD) is characterized by beta-amyloid (Aβ) plaques in the brain and widespread neuronal damage. Because of the high drug attrition rates in AD, there is increased interest in characterizing neuroimmune responses to Aβ plaques. In response to AD pathology, microglia are innate phagocytotic immune cells that transition into a neuroprotective state and form barriers around plaques. We seek to understand the role of microglia in modifying Aβ dynamics and barrier formation. To quantify the influence of individual microglia behaviors (activation, chemotaxis, phagocytosis, and proliferation) on plaque size and barrier coverage, we developed an agent-based model to characterize the spatiotemporal interactions between microglia and Aβ. Our model qualitatively reproduces mouse data trends where the fraction of microglia coverage decreases as plaques become larger. In our model, the time to microglial arrival at the plaque boundary is significantly negatively correlated (p < 0.0001) with plaque size, indicating the importance of the time to microglial activation for regulating plaque size. In addition, in silico behavioral knockout simulations show that phagocytosis knockouts have the strongest impact on plaque size, but modest impacts on microglial coverage and activation. In contrast, the chemotaxis knockouts had a strong impact on microglial coverage with a more modest impact on plaque volume and microglial activation. These simulations suggest that phagocytosis, chemotaxis, and replication of activated microglia have complex impacts on plaque volume and coverage, whereas microglial activation remains fairly robust to perturbations of these functions. Thus, our work provides insights into the potential and limitations of targeting microglial activation as a pharmacological strategy for the treatment of AD.

Minimum Cost Deployment of Bistatic Radar Sensors for Perimeter Barrier Coverage of Critical Square Grids

Minimum Cost Deployment of Bistatic Radar Sensors for Perimeter Barrier Coverage of Critical Square Grids

Cuckoo search algorithm-based optimal deployment method of heterogeneous multistatic radar for barrier coverage

This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions. This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence. Based on these properties and considering location restrictions, it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars. To overcome the non-convexity of the model and the non-analytical nature of the objective function, an algorithm combining integer line programming and the cuckoo search algorithm (CSA) is proposed. The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost. Simulations are conducted in different conditions to verify the effectiveness of the proposed method.

AutoBar: Automatic Barrier Coverage Formation for Danger Keep Out Applications in Smart City.

Barrier coverage is a fundamental application in wireless sensor networks, which are widely used for smart cities. In applications, the sensors form a barrier for the intruders and protect an area through intrusion detection. In this paper, we study a new branch of barrier coverage, namely warning barrier coverage (WBC). Different from the classic barrier coverage, WBC has the inverse protect direction, which moves the sensors surrounding a dangerous region and protects any unexpected visitors by warning them away from the dangers. WBC holds a promising prospect in many danger keep out applications for smart cities. For example, a WBC can enclose the debris area in the sea and alarm any approaching ships in order to avoid their damaging propellers. One special feature of WBC is that the target region is usually dangerous and its boundary is previously unknown. Hence, the scattered mobile nodes need to detect the boundary and form the barrier coverage themselves. It is challenging to form these distributed sensor nodes into a barrier because a node can sense only the local information and there is no global information of the unknown region or other nodes. To this end, in response to the newly proposed issue of the formation of barrier cover, we propose a novel solution AutoBar for mobile sensor nodes to automatically form a WBC for smart cities. Notably, this is the first work to trigger the coverage problem of the alarm barrier, wherein the regional information is not pre-known. To pursue the high coverage quality, we theoretically derive the optimal distribution pattern of sensor nodes using convex theory. Based on the analysis, we design a fully distributed algorithm that enables nodes to collaboratively move toward the optimal distribution pattern. In addition, AutoBar is able to reorganize the barrier even if any node is broken. To validate the feasibility of AutoBar, we develop the prototype of the specialized mobile node, which consists of two kinds of sensors: one for boundary detection and another for visitor detection. Based on the prototype, we conduct extensive real trace-driven simulations in various smart city scenarios. Performance results demonstrate that AutoBar outperforms the existing barrier coverage strategies in terms of coverage quality, formation duration, and communication overhead.

An Efficient Anti-Intrusion Detection Algorithm Based on MEP for Directional Sensor Networks

In wireless sensor networks(WSNs), the minimum exposure path (MEP) represents the worst coverage of the whole network, so the exploration of MEP is of great significance to prevent unauthorized objects from passing through the monitoring area. The traditional research on finding MEP only focuses on how to avoid actual obstacles, without considering how to avoid high coverage areas. MEP-based coverage optimization studies the scheme of directly adding nodes, which does not conform to the characteristics that WSNs nodes are difficult to add or replace once deployed. In order to effectively improve the monitoring ability of coverage area, this paper proposes an efficient anti-intrusion detection algorithm based on MEP for directional sensor networks. Firstly, in the stage of finding MEP, the relationship between ant colony path planning algorithm and MEP is constructed by using dynamic threshold strategy. Secondly, in order to find MEP more accurately, the exposure factor is added to the state transition probability formula of the original ant colony algorithm. Finally, in the coverage enhancement stage, this paper innovatively proposes a barrier coverage enhancement strategy, which constructs a barrier by adjusting the position of redundant nodes. The simulation results show that the MEP found in this paper accurately avoids the high coverage area, and the improved ant colony algorithm is better than the MEP found by the original ant colony algorithm. Compared with the baseline algorithm, the barrier coverage enhancement strategy has strong applicability and low cost, which significantly improves the network monitoring ability.

Optimal algorithm for min-max line barrier coverage with mobile sensors on 2-dimensional plane

Emerging IoT applications impose line barrier coverage (LBC) tasks with min–max movement objective due to requirements of energy balance, fairness, etc. In LBC, we are given a line barrier and a set of n sensors distributed on the plane. The aim is to move the sensors to fully cover the given barrier, such that the maximum movement of the mobile sensors is minimized and hence the energy consumption of the sensors are balanced. This paper proposes an exact algorithm to optimally solve LBC, which deserves a runtime On2 compared favorably to the previous state-of-art runtime On2logn. The key idea of the improvement is acceleration-via-approximation: devise a novel approximation algorithm and then use it to accelerate the calculation of optimum solutions. Extensive numerical experiments were carried out to evaluate the practical performance of our algorithm against other baselines, demonstrating its performance gain over the previous state-of-art algorithms.

Optimization method of linear barrier coverage deployment for multistatic radar

To address the problem of building linear barrier coverage with the location restriction, an optimization method for deploying multistatic radars is proposed, where the location restriction splits the deployment line into two segments. By proving the characteristics of deployment patterns, an optimal deployment sequence consisting of multiple deployment patterns is proposed and exploited to cover each segment. The types and numbers of deployment patterns are determined by an algorithm that combines the integer linear programming (ILP) and exhaustive method (EM). In addition, to reduce the computation amount, a formula is introduced to calculate the upper threshold of receivers' number in a deployment pattern. Furthermore, since the objective function is non-convex and non-analytic, the overall model is divided into two layers concerning two suboptimization problems. Subsequently, another algorithm that integrates the segments and layers is proposed to determine the deployment parameters, such as the minimum cost, parameters of the optimal deployment sequence, and the location of the split point. Simulation results demonstrate that the proposed method can effectively determine the optimal deployment parameters under the location restriction.

Improved genetic algorithm-based sensor nodes deployment for barrier coverage

Improved genetic algorithm-based sensor nodes deployment for barrier coverage

Improved genetic algorithm based sensor nodes deployment for barrier coverage

Improved genetic algorithm based sensor nodes deployment for barrier coverage

Approximation algorithm for MinSum linear barrier coverage with sink-based mobile sensors on the plane

Emerging wireless and mobile applications, such as border intrusion detection with station-based drones, brought a new barrier coverage problem of using sink-based mobile sensors to cover a given line barrier with minimum energy consumption. In this paper, we focus on the uniform sink-based line barrier coverage (SLBC) problem, in which we are given a line barrier and k sink stations distributed on the plane which can emit an infinite number of sensors with an identical sensing radius. The problem aims to find their final positions on the barrier for the sensors emitted by the stations, such that the total moving distance of the sensors is minimized and each point of the barrier is within the sensing area of at least one sensor. We first observe the geometric structure of an optimal solution that any optimal solution can be considered as a set of intersecting tangent (disk) segments, where a tangent (disk) segment is a sequence of tangent disks. Then, we devise an algorithm to calculate all possible tangent (disk) segments and another algorithm to calculate the near-optimal positions for each of such segments. After computing all tangent (disk) segments and their near-optimal positions, an algorithm is proposed to transform uniform SLBC into an instance of the shortest path problem. It is shown the whole algorithm deserves a runtime O(k2log⁡krε) and consumes at most ε more movement than an optimal solution, where ε is any given positive real number, and r and k are the sensor radius and the number of sink stations, respectively.

Anti–Cholestatic Therapy with Obeticholic Acid Improves Short-Term Memory in Bile Duct–Ligated Mice

Patients with cholestatic liver disease, including those with primary biliary cholangitis, can experience symptoms of impaired cognition or brain fog. This phenomenon remains unexplained and is currently untreatable. Bile duct ligation (BDL) is an established rodent model of cholestasis. In addition to liver changes, BDL animals develop cognitive symptoms early in the disease process (before development of cirrhosis and/or liver failure). The cellular mechanisms underpinning these cognitive symptoms are poorly understood. Herein, the study explored the neurocognitive symptom manifestations, and tested potential therapies, in BDL mice, and used human neuronal cell cultures to explore translatability to humans. BDL animals exhibited short-term memory loss and showed reduced astrocyte coverage of the blood-brain barrier, destabilized hippocampal network activity, and neuronal senescence. Ursodeoxycholic acid (first-line therapy for most human cholestatic diseases) did not reverse symptomatic or mechanistic aspects. In contrast, obeticholic acid (OCA), a farnesoid X receptor agonist and second-line anti-cholestatic agent, normalized memory function, suppressed blood-brain barrier changes, prevented hippocampal network deficits, and reversed neuronal senescence. Co-culture of human neuronal cells with either BDL or human cholestatic patient serum induced cellular senescence and increased mitochondrial respiration, changes that were limited again by OCA. These findings provide new insights into the mechanism of cognitive symptoms in BDL animals, suggesting that OCA therapy or farnesoid X receptor agonism could be used to limit cholestasis-induced neuronal senescence.

S1779 A Peculiar Case of Jaundice and Renal Failure After Hurricane Ida

Introduction: Leptospirosis is a zoonotic disease seen in tropical and temperate regions, with roughly 1.03 million cases worldwide and 58,900 deaths annually. Humans are infected when exposed to the tissue or urine of colonized rodents, cattle, swine, dogs, or sheep. The symptoms are nonspecific but include fever, myalgia, and rigors. Laboratory findings in severe cases include hyponatremia, elevated hepatic enzymes, renal failure, and thrombocytopenia. Transaminases are typically mildly elevated, but total bilirubin can increase to as high as 80 mg/dL. The associated jaundice is thought to be due to hepatocellular necrosis, intrahepatic cholestasis, and absorption of tissue hemorrhage. In severe cases of jaundice and renal failure, “Weil's Disease” is diagnosed. Case Description/Methods: Hurricane Ida produced record rainfall in the northeastern US over an 18 hour period. Five days following the storm, a 52 year old male with no significant past medical history, presented to our ER complaining of fever, night sweats, chills, fatigue, and generalized weakness. For work, he had been tasked to clear pools of stagnant water from normally dry areas of urban parks. On presentation, his blood pressure was 136/68 mmHg, heart rate 159 bpm, temperature 36.4 degrees C, and oxygen saturation of 95% on room air. His exam was notable for scleral icterus, jaundice, and tachycardia. The abdomen was soft, non-tender and non-distended, and without hepatomegaly. Laboratory values are given in the Table. The patient’s renal failure subsequently worsened with BUN/creatinine reaching 114/7.48 mg/dL. Abdominal ultrasound and MRCP demonstrated no abnormalities. On day 4 urine DNA for Leptospira was positive, though serum Leptospira PCR was negative. He was started on doxycycline and ceftriaxone with improvement in his symptoms, jaundice and renal failure. Discussion: Leptospira is endemic in mostly southern and Pacific coastal areas of the US, as well as Hawaii. In developed countries, leptospirosis is commonly seen after heavy rainfall and floods. Over the past 5 years, locally acquired cases of leptospirosis have surpassed travel associated infection in our local jurisdiction. Climate studies have pointed to a positive correlation between cases of leptospirosis and significant changes in climate and associated flooding. Given the potential severity of leptospirosis, community education to avoid stagnant water and barrier coverage in emerging Leptospirosis hotspots could be beneficial in the prevention of disease. Table 1. - Relevant Labs from Admission Hemoglobin 14.3 g/dL Platelets 68,000 u/L MCV 84 fL ESR 58 ml/Hr BUN / Cr 54 mg/dL / 2.9 mg/dL Sodium 129 mmol/L Total Bilirubin 6.7 mg/dL Direct Bilirubin 5.08 mg/dl ALT 78 unit/L AST 191 unit/L Alkaline Phosphatase 102 unit/L CPK 3,600 unit/L Lipase 2.3 unit/L Hepatitis A,B,C serology evidence of prior HBV vaccination Ds-DNA within normal limits Immunoglobin A,G,E,M within normal limits

Lifetime-Maximized Strong Barrier Coverage of 3D Camera Sensor Networks

Camera sensor networks (CSNs) have advantages on providing the precise and multimedia information for plenty of applications. The high coverage quality of CSNs especially satisfies the monitoring requirements of barrier coverage. In three-dimensional (3D) application scenarios, the tracking of the potential intruder in the monitored irregular spaces brings more difficulties and challenges on strong barrier coverage for CSNs. In this paper, we consider the strong barrier coverage problem in 3D CSNs and focus on the objective of monitoring the intruder with high resolution and maximizing the network lifetime. We firstly introduce the definition and hardness proof for the problem based on the irregular space model and the network model, which adopts the Region of Interest (ROI) sensing model with high effective resolution. Secondly, we design two sleep-and-awake scheduling algorithms for the problem in homogeneous and heterogeneous networks, respectively, which are based on the auxiliary graph transformation and the disjoint flows construction. To evaluate these algorithms’ performance on the lifetime maximization, we conduct extensive simulation experiments and analyze their results on their advantages and applicable scenarios.

A cluster-based barrier construction algorithm in mobile Wireless Sensor Networks

It is important to maximize network lifetime while meeting coverage requirements in Wireless Sensor Networks (WSN). This paper focuses on maximizing the network lifetime of barrier coverage in WSN with mobile sensors. For mobile sensors, movement energy consumption can be much higher than during sensing and communication. Since the battery capacity of the sensor is fixed, more energy can be used for sensing and communication if the movement distance required to build the barrier can be reduced. Therefore, we focus on reducing the movement distance required by the mobile sensors to build the barriers. Also, we can build as many barriers as possible if we use as few mobile sensors as possible to build a barrier. By rotating multiple barriers, we can further extend the lifetime of the network. Based on the above concept, an energy-efficient algorithm is proposed for building barriers in WSNs with mobile sensors. The contribution of this paper are: (1) We find the minimum number of sensors required to construct a barrier for a rectangular region. (2) We explain how to cluster the sensors in the region, and then calculate the linear equations of the barriers based on the results of the clustering. (3) We explain how to set the sojourn points for these linear equations of the barriers, and then assign the mobile sensors to every one of these sojourn points. In short, the proposed algorithm can construct multiple barriers depending on the location of the sensor, with a minimum number of sensors connecting the left and right boundaries of the target field. Finally, the simulation results show that the proposed algorithm has better performance in terms of network lifetime than the previous result.

Min–max movement of barrier coverage with sink-based mobile sensors for crowdsensing

Emerging crowdsensing applications imposed a new barrier coverage problem called min–max sink-based linear barrier coverage (min–max SLBC). In the problem, we are given a group of sinks distributed on a plane, each of which can disseminate an infinite number of nonuniform mobile sensors. The aim is to cover a given linear barrier using mobile sensors disseminated from the sinks, such that the maximum energy consumed by sensor movement is minimized. We devise a polynomial algorithm for min–max SLBC with nonuniform sensors, despite the sensor-based linear barrier coverage counterpart of the problem was proven strongly NP-hard. To this end, we first present a polynomial-time algorithm, namely Separated Target Coverage Algorithm (STCA), for optimally solving the discretized version of min–max SLBC. Then we devise the exact algorithm called Segment Collaborative-Coverage Algorithm (SCCA) for the continuous version of min–max SLBC, by improving an approximate solution computed by STCA to eventually obtain an arguably optimal solution. Lastly, numerical experiments are carried out to validate the efficiency and effectiveness of SCCA via comparing with other baselines including the state-of-art algorithms.

JSQE: Joint Surveillance Quality and Energy Conservation for Barrier Coverage in WSNs

Barrier coverage is a fundamental issue in wireless sensor networks (WSNs). Most existing works have developed centralized algorithms and applied the Boolean Sensing Model (BSM). However, the critical characteristics of sensors and environmental conditions have been neglected, which leads to the problem that the developed mechanisms are not practical, and their performance shows a large difference in real applications. On the other hand, the centralized algorithms also lack scalability and flexibility when the topologies of WSNs are dynamically changed. Based on the Elfes Sensing Model (ESM), this paper proposes a distributed Joint Surveillance Quality and Energy Conservation mechanism (JSQE), which aims to satisfy the requirements of the desired surveillance quality and minimize the number of working sensors. The proposed JSQE first evaluates the sensing probability of each sensor and identifies the location of the weakest surveillance quality. Then, the JSQE further schedules the sensor with the maximum contribution to the bottleneck location to improve the overall surveillance quality. Extensive experiment results show that our proposed JSQE outperforms the existing studies in terms of surveillance quality, the number of working sensors, and the efficiency and fairness of surveillance quality. In particular, the JSQE improves the surveillance quality by 15% and reduces the number of awake sensors by 22% compared with the relevant TOBA.

Maximizing barrier coverage lifetime with static sensors

Maximizing barrier coverage lifetime with static sensors

Optimal deployment of multistatic radar for belt barrier coverage

Optimal deployment of multistatic radar for belt barrier coverage