Evaluating coverage quality through best covered pathes in wireless sensor networks

Node placement for connected target coverage in wireless sensor networks with dynamic sinks

Efficient coverage and connectivity are two important factors that ensures better service quality especially during tracking targets or monitoring events in wireless sensor network. Although massive amount of studies has been carried out in the past to enhance coverage and connectivity issues, till date very few studies have witnessed a significant and standard outcomes that can opt further. Hence, this paper introduces a computationally efficient technique for jointly addressing both coverage and connectivity problems in large-scale wireless sensor network that ensures optimal network lifetime too. The proposed system has been empirically designed, and algorithms formulated to ensure energy efficient monitoring of event. The outcomes of the study are compared with standard energy efficient hierarchical protocol to benchmark the results.

Parallel and distributed computing has been the basis to many emerging areas, such as smart networks, cloud computing, big data analysis, and blockchain technology. Without the development of parallel and distributed computing technologies and various types of systems, it is not possible to meet the requirement on efficiency, accuracy, scalability, and reliability for various critical applications that support our modern economy and society. While parallel and distributed computing played a vital role in modern science, engineering, biology, medicine, pharmacy, astronomy, geology, and archaeology, its application has also been extended to business, finance, economics, management, government, and defense, covering all aspects of our modern society and life. Furthermore, parallel and distributed computing has emerged in recent advances of many hotspot research directions including artificial intelligence, machine learning, Internet of Things, bioinformatics, digital medicine, cybersecurity, and social computing, resulting in numerous ground-breading discoveries that are changing our society and life.

Many wireless sensor network applications must resolve the inherent conflict between energy efficient and nodes of coverage in wireless sensor networks to achieve desired quality of service (QoS). The wireless sensor networks (WSNs) have been the main focus in the past few years, and it is becoming a special issue. We study the problem of controlling the node locations and energy within ad-hoc sensor networks. Network survivability is a very important measure for deciding the efficiency of network protocols. It includes a measure of the network lifetime as well as the quality of service. In fact, these dynamics are very important in evaluating networks. The wireless network applications can be found in battlefield communication, homeland security, pollution sensing and traffic monitoring. As such, there has been an increasing need for defining and developing simulation frameworks for carrying out high-fidelity WSN simulation. In this cause, we present a simulation by including factors such as energy-consumption, Bandwidth, nodes, and coverage and provides an object-oriented definition of target, sensor and sink nodes, sensor and wireless communication nodes, and physical radio such as relating of nodes, mobility model and power model both energy-producing and energy-consuming components, the simulation was developed using C#.

To provide proper coverage of their random deployment regions, wireless sensor networks (WSN) should employ abundant nodes. In this paper we correct such situations by employing some mobile robots as mobile nodes in WSN which can actively move to desired locations for repairing the broken networks. According to the pre-research work we know that the number of nodes employed by WSN is closely relevant to quality of service (QoS) in sensing coverage when the nodes are randomly deployed in the target region. A modified particle swarm optimization (PSO) named particle swarm genetic optimization (PSGO), which imports selection and mutation operators in PSO to overcome the premature fault of classical PSO, is proposed to redeploy the mobile robots according to the node density for repairing the sensing coverage hole after their initial random deployment. It is suggested by the simulated experiment results that the WSN employing the mobile robots can improve the QoS in sensing coverage than the stationary WSN by redeploying mobile robots according to the node density.

Coverage in wireless sensor networks is a critical issue since it reflects the cost and detection capability of the network. Sensor coverage model is closely to the sensing functions of different types of sensors while network coverage is a collaborative measure from geographically distributed sensors. The coverage problems in wireless sensor networks have been formulated in various ways with different assumptions, constraints and objectives. In this work, a collaborative coverage model is proposed in the target surveillance application, while sensor sensing probabilistic model is introduced. Furthermore, a collaborative target coverage optimization algorithm (CTCOMSN) is presented to prolong the network lifetime in energy constraint mobile sensor networks. Simulation results show that CTCOMSN can prolong the lifetime greatly while improving the sensing quality.

Target Coverage and Network Connectivity in Wireless Sensor Networks (WSNs) plays a momentous role in the field of monitoring environment, habitant observing, disaster recovery, surveillance, etc. Coverage and Network Connectivity collectively can be considered as a proportion of Quality of Service (QoS) in a sensor network. It implies the coverage of each point in the detecting field while in the meantime fulfilling the measure that each node is surrounded by the equivalent neighbourhood of at least one other node. Many primary issues influence the outline and performance of WSN. A Comprehensive survey is made based on the scheduling algorithm and set cover approach, in which we analyze various approaches and their algorithm complexity. Firstly, the scheduling algorithm intermittently provides the required data service with guaranteed efficiency. This methodology can efficiently reduce the entire number of active nodes in the network, resulting in maximizing the network lifetime. Secondly, the set cover approach plays a major role in solving target coverage problem which group sensors into each cover set thereby, target coverage was achieved. Typical issues and open research challenges are addressed by classifying the approaches available in literature into three broad categories namely, adaptable coverage radius, coverage deployment strategy, and sleep scheduling. This survey aims to provide a better perceptive of the existing open challenges and possible futuristic approaches for target coverage and network connectivity in wireless sensor networks.

Wireless sensor networks are a collection of specially designed nodes to provide support to sensor information propagation. Sensor nodes are basically designed to sense data as sensor and distribute to servers for further analysis. Based on the specific requirements, the numbers of sensor nodes can range from hundreds to thousands. All the communication will take place through predefined network characteristics. WSNs generally face energy issues. LEACH is designed for efficient cluster formation. It provides an efficient energy solution for data transmission from node to base station. Various enhanced version of LEACH has been proposed by Assuming LEACH as base protocol. The energy constraints are a critical aspect in developing the routing protocols for WSNs. Designers and researchers have contributed their effort through enhancement in energy saving procedure into WSNs. In this work, the LEACH based protocols and their performance in WSN has been analysed. This research paper evaluates recent advancement in LEACH based approaches for Wireless Wide Area Sensor Network with comparison table.

Although most of the studies on coverage and connectivity in wireless sensor networks (WSNs) considered two-dimensional (2D) settings, such networks can in reality be accurately modeled in a three-dimensional (3D) space. The concepts of continuum percolation theory best fit the problem of connectivity in WSNs to find out whether the network provides long-distance multihop communication. In this paper, we focus on percolation in coverage and connectivity in 3D WSNs. We say that the network exhibits a coverage percolation (respectively, connectivity percolation) when a giant covered region (respectively, giant connected component) almost surely spans the entire network for the first time. Because of the dependency between coverage and connectivity, the problem is not only a continuum percolation problem but also an integrated continuum percolation problem. Thus, we propose an integrated-concentric-sphere model to address coverage and connectivity in 3D WSNs in an integrated way. First, we compute the critical density lambdaC con above which coverage percolation in 3D WSNs will almost surely occur. Second, we compute the critical density lambdac con above which connectivity percolation in 3D WSNs will almost surely occur. Third, we compute the critical density lambdac cov-con above which both coverage and connectivity percolation in 3D WSNs will almost surely occur. For each of these three problems, we also compute their corresponding critical network degree. Our results can be helpful in the design of energy-efficient topology control protocols for 3D WSNs in terms of coverage and connectivity.

Aiming at the uneven random coverage distribution of wireless sensor networks sensor nodes, the sparrow search algorithm (SSA) is used to optimize the node coverage of wireless sensor networks. To improve the global search capability of SSA, the algorithm is improved and applied to the wireless sensor networks of bridge monitoring. For enhancing the coverage of the wireless sensor networks, this article uses two improved methods. One is to use the good point set theory to make the initial population evenly distributed; another is to introduce a weight factor to speed up its convergence. The experiments have proved the reliability and rationality of the algorithm. The improved algorithm is superior to other meta-heuristic algorithms and provides a new idea for optimizing bridge monitoring wireless sensor networks coverage.

In this paper, we consider the problem of wireless sensors deployed in a circular area to achieve a desired degree of coverage. To this end, we propose a coverage algorithm based on polar coordinates to enhance the coverage after an initial random deployment. The desired positions of neighbor nodes along different directions are defined, Thus, the virtual radius and the virtual angle of a sensor node in the polar coordinate plane are calculated, and then the sensor node moves to the desired position in the radial direction and the circumferential direction, respectively. We adjust the nodes' polar coordinates via their radii and angles (in node ID sequence as much as possible) to reduce overlap in the node sensing area and improve the coverage of Wireless Sensor Networks (WSNs).

Notice of Violation of IEEE Publication Principles Critical Density for Coverage and Connectivity in Two-Dimensional Aligned-Orientation Directional Sensor Networks Using Continuum Percolation, by Mohammad Khanjary, Masoud Sabaei, and Mohammad Reza Meybodi in IEEE Sensors Journal, vol. 14, no. 8, pp. 2856-2863, Aug. 2014 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. Integrated Coverage and Connectivity in Wireless Sensor Networks: A Two-Dimensional Percolation Problem, by H. M. Ammari and S. K. Das, in IEEE Transactions on Computers, vol. 57, no. 10, pp. 1423-1434, Oct. 2008 Sensing coverage is one of the fundamental design issues in wireless sensor networks, which reflects the surveillance quality provided by them. Moreover, network connectivity enables the gathered data by sensors to reach to the sink node. Given an initially uncovered field, and as more and more directional sensors are continuously added to the sensor network, the size of partial covered areas increases. At some point, the situation abruptly changes from small fragmented covered areas to a single large covered area. We call this abrupt change the sensing-coverage phase transition (SCPT). Likewise, given an originally disconnected sensor network, as more and more sensors are added, the number of connected components changes such that the sensor network suddenly becomes connected at some point. We call this sudden change the network connectivity phase transition (NCPT). The nature of such phase transitions is a central topic in the percolation theory. In this paper, we introduce aligned-orientation directional sensor networks in which nodes are deployed based on Poisson point process and the orientation of all sensor nodes is the same. Then, we propose an approach to compute density of nodes at critical percolation for both of the SCPT and NCPT problems in such networks, for all angles of field-of-view between 0 and π by using continuum percolation. Due to percolation theory, the critical density is infimum density that for densities above it SCPT and NCPT almost surely occur. In addition, we propose a model for percolation in directional sensor networks, which provides a basis for solving the SCPT and NCPT problems together.

Wireless Sensor Networks (WSNs) can be used effectively to form barriers that monitor strips of land for applicaions such as homeland security and critical infrastructure protection. Sensors are highly constrained in their energy usage, so when they harvest energy, it is neccessary that this energy be used effectively. 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. The lifetime problem for WSNs has been studied extensively. In this paper we give an exact solution to the problem of achieving maximum lifetime for the application of k-barrier coverage in energy harvesting wireless sensor networks.

Forest fire detection system using barrier coverage in wireless sensor networks

This paper investigates the benefits of spatial correlation for the problem of coverage in Wireless Sensor Networks (WSN). Specifically, it studies two detectors, the Mean Detector (MD) and the Covariance Detector (CD) and compares their coverage performance for various scenarios. The main contribution of this paper is to show that one can exploit the possible correlation between measurements of neighboring sensor nodes in order to achieve significantly better coverage. Moreover, the results of this paper have direct implications on the topology of the network. Our results indicate that for the CD the best placement would be pairs of sensor nodes placed on a grid configuration.