Connectivity In Sensor Networks Research Articles

ДОСЛІДЖЕННЯ ЗАДАЧ ПОБУДОВИ БЕЗДРОТОВИХ СЕНСОРНИХ МЕРЕЖ

The research of problems of construction of wireless sensor networks is carried out in the work, the main stage of their decision is development of models of the description of a sensor network and the corresponding methods, technologies of maintenance of necessary parameters of quality of functioning of a sensor network. The study involves the consideration of basic technologies and standards in which there is an opportunity to implement the creation of wireless sensor networks. The basis of wireless sensor networks are communication channels organized between network elements using appropriate wireless technology. The main tasks of building wireless sensor networks: determining traffic parameters; determining the list of services; development or selection of a network model; determination of network functioning indicators; solving the problem of compromise between the quality of operation, traffic and resources. A number of wireless networking technologies are widespread in corporate networks, use an unlicensed frequency band, and in private networks, which allows their use in a number of tasks, due to the density of devices that support them and the availability of technology. A number of technologies do not support the functions of self-organization of the communication network. Such mechanisms can be implemented using software and related protocols at the network level. Existing technologies have the ability to organize communication from tens to tens of thousands of meters. For specific applications, it is one of the essential factors in choosing the appropriate technology. The probability of connectivity in wireless sensor networks depends on the structure and parameters that determine the network: characteristics of the service area (volume, flat, configuration, geometric dimensions), number of network nodes, characteristics of communication capabilities of network elements, antenna patterns, standards and protocols, communication range, transmitter power), features of the involved routing protocols. Features of providing connectivity in wireless sensor networks lie in the possibility of using gateways built using various technologies, which can significantly expand the capabilities of wireless networks in increasing the likelihood of connectivity. A feature of the construction of wireless sensor networks are significant differences in traffic servicing in the networks of different technologies used. Indicators of the quality of wireless networks, such as bandwidth, delay, probability of loss are interdependent and show how effectively the sensor network works. When you change one of the performance indicators of wireless sensor networks, it affects other quality indicators.

Modified Floyd–Warshall’s Algorithm for Maximum Connectivity in Wireless Sensor Networks under Uncertainty

The main objective of this paper is to find the duration of maximum time connectivity of sensor nodes under uncertainty utilizing the prespecified voltage/power of each sensor node. Wireless sensor networks (WSNs) are composed of nodes that transmit data between each other over routing. A variety of routing protocols and algorithms exist, each related to a particular set of conditions. There are a variety of routing algorithms available, some of which can be used in WSNs for routing. The goal of the fastest distance routing algorithms in a WSN is to use the least amount of energy possible. In a WSN, Dijkstra’s algorithm is typically used for shortest path routing. The Floyd–Warshall’s algorithm is used to compute the shortest paths between distinct nodes in a regular graph, but due to the absence of a communication mode, this algorithm is not ideal for routing in wireless networks. In this research work, we have considered a WSN to find out the maximum connectivity time utilizing optimum voltage. On the other hand, duration of connectivity and energy/voltage are two vital parameters that are difficult to manage. Because of limited resources and safety concerns, safety implementation is limited. Also, due to the irregular/hazardous environmental situations, the distance between sensor nodes and its voltage to link up the nodes are totally unpredictable. In this work, we employ triangular fuzzy numbers to express unpredictability. Then, utilizing defuzzification of fuzzy numbers, the associated WSN problem was transformed into a crisp one. The widely used signed distance approach has been applied for the defuzzification of fuzzy numbers in this case. To determine the best outcome and to illustrate the usefulness of the suggested technique, a numerical example has been solved using the modified Floyd–Warshall’s algorithm. Finally, concluding remarks on the proposed approach as well as future studies have been provided.

Memetic Algorithm based Energy Efficient Wake-up Scheduling Scheme for Maximizing the Network Lifetime, Coverage and Connectivity in Three-Dimensional Wireless Sensor Networks

Memetic Algorithm based Energy Efficient Wake-up Scheduling Scheme for Maximizing the Network Lifetime, Coverage and Connectivity in Three-Dimensional Wireless Sensor Networks

Design of energy‐efficient intermittently connected sensor networks

This paper introduces the concept of intermittently connected sensor networks where sensors are sleep most of time and become active randomly and rarely. In the networks, packet collision probability and power consumption can be reduced. Meanwhile, the delivery delay increases with the use of the low activation values. In this paper, we design the energy‐efficient intermittently connected sensor networks, considering this trade‐off of activation control. We first provide the algorithm that computes the optimal packet forwarding rule achieving the minimum delivery delay, which can be calculated using the activation rates. We then propose the activation rate control methods, which control the activation rates of the sensors based on the density of the sensors and/or the number of wake‐ups of sensors having relay packets. By doing this, we can improve the delay performance, while suppressing the increase in the packet collision probability and the power consumption of sensors. Through simulation experiments, we demonstrate the effectiveness of our activation control methods in the intermittently connected sensor networks. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Connectivity and Coverage in Hybrid Wireless Sensor Networks using Dynamic Random Geometric Graph Model

Connectivity and Coverage in Hybrid Wireless Sensor Networks using Dynamic Random Geometric Graph Model

C-TOL: Convex triangulation for optimal node localization with weighted uncertainties

There is always a need to reduce localization error in any wireless sensor network (WSN), and our aim is to observe the impact of localization uncertainty on network awareness. When nodes are deployed in a 2D plane and their l2-norm ranged triangulations are found, usually the unweighted localization uncertainty values become absurdly large with large triangulation cases. Moreover, there is no regard for the disparity between the lengths of any two links on the localization uncertainty. The upper bound of uncertainty keeps on rising with formation of asymmetric node triangulations with longer internodal distances and sharper vertices. To address this gap, a convex combination weighted approach (C-TOL, standing for Convex-Triangulation for Optimal node Localization) for solving the localization uncertainty problem is described here. The advantage of the proposed method is shown with the help of rigorous mathematical analysis of weighted uncertainty behaviour. The relationship of sensor node symmetry with triangulation uncertainty is formulated algebraically by considering both symmetric as well as asymmetric triangulations. Cramer Rao bound is derived to justify estimation under triangulation uncertainty. This approach paves the way for the WSN to prioritize different kinds of triangulations. Numerical results reveal that the weighted method prefers triangulations with more symmetry; hence it consistently achieves significantly lower values of mean and standard deviations than the existing unweighted localization technique, especially for densely connected sensor networks. Moreover, the proposed method shows robust localization performance for sparsely deployed networks as well, when compared to recent methods in literature.

An Efficient Approach for Big Data Aggregation Mechanism in Heterogeneous Wireless Connected Sensor Networks

Recently and due to the impressive growth in the amounts of transmitted data over the heterogeneous sensor networks and the emerged related technologies especially the Internet of Things in which the number of the connected devices and the data consumption are remarkably growing, big data has emerged as a widely recognized trend and is increasingly being talked about. The term big data is not only about the volume of data, but also refers to the high speed of transmission and the wide variety of information that is difficult to collect, store and process using the available classical technologies. Although the generated data by the individual sensors may not appear to be significant, all the data generated through the many sensors in the connected sensor networks are able to produce large volumes of data. Big data management imposes additional constraints on the wireless sensor networks and especially on the data aggregation process, which represents one of the essential paradigms in wireless sensor networks. Data aggregation process can represent a solution to the problem of big data by allowing data from different sources to be combined to eliminate the redundant ones and consequently reduce the amounts of data and the consumption of the available resources in the network. The main objective of this work is to propose a new approach for supporting big data in the data aggregation process in heterogeneous wireless sensor networks. The proposed approach aims to reduce the data aggregation cost in terms of energy consumption by balancing the data loads on the heterogeneous nodes. The proposal is improved by integrating the feedback control closed loop to reinforce the balance of the data aggregation load on the nodes, maintaining therefore an optimal delay and aggregation time.

Lattice‐Based 3‐Dimensional Wireless Sensor Deployment

With the wide application of wireless sensor networks (WSNs) in real space, there are numerous studies on 3D sensor deployments. In this paper, the k‐connectivity theoretical model of fixed and random nodes in regular lattice‐based deployment was proposed to study the coverage and connectivity of sensor networks with regular lattice in 3D space. The full connectivity range and cost of the deployment with sensor nodes fixed in the centers of four regular lattices were quantitatively analyzed. The optimal single lattice coverage model and the ratio of the communication range to the sensing range (rc/rs) were investigated when the deployment of random nodes satisfied the k‐connectivity requirements for full coverage. In addition, based on the actual sensing model, the coverage, communication link quality, and reliability of different lattice‐based deployment models were determined in this study.

Retracted] Low‐Latency and High‐Concurrency 5G Wireless Sensor Network Assists Innovation in Ideological and Political Education in Colleges and Universities

This paper first analyzes the existing optimization models and methods based on low‐latency and high‐concurrency 5G wireless sensor networks and focuses on some research results based on the physical layer, data link layer, and network layer. After that, the energy‐constrained cross‐layer optimization algorithm of the joint physical layer and network layer and the cross‐layer optimization algorithm based on reliable transmission are analyzed and compared. According to the ideological and political education cycle and network connectivity of wireless sensor networks, the existing definition of the ideological and political education cycle of wireless sensor networks was questioned and its irrationality was demonstrated. Firstly, we introduce the system model, energy capture model, and energy consumption model of this scheme; then, calculate the energy consumption of the node sending and receiving data and analyze the maximum throughput that the node can provide for data transmission to perform mathematical modeling. In a balanced ideological and political education cycle, the optimal solution is given. Finally, it introduces distributed high‐throughput routing for EH‐WSNs based on low latency and high concurrency and gives a performance comparison with the shortest path routing scheme. The energy consumption of each part of the node is analyzed in a comprehensive and in‐depth manner, and the direction of the energy optimization strategy of the network node and its sensor network is pointed out. On this basis, this article proposes a new definition of the network ideological and political education cycle: the ideological and political education cycle of the wireless sensor network is equal to the ideological and political education cycle of the first joint in the network that fails due to energy exhaustion. Based on this definition, the wireless sensor network is analyzed, and the cross‐layer (physical layer, data link layer, and network layer) optimization mathematical model of the wireless sensor network ideological and political education cycle is established. The two data collection schemes proposed in this paper are simulated under the conditions of no‐delay ideological and political education cycle and different time‐delayed ideological and political education cycles. The simulation results show that the model is better than both in terms of network life and data integrity.

A fault tolerant algorithm for integrated coverage and connectivity in wireless sensor networks

There are two major requirements for any surveillance application using wireless sensor networks (WSN) - coverage and connectivity. In the design of such an application, a major constraint is limit...

A fault tolerant algorithm for integrated coverage and connectivity in wireless sensor networks

A fault tolerant algorithm for integrated coverage and connectivity in wireless sensor networks

Energy efficient scheme for better connectivity in sustainable mobile wireless sensor networks

The extreme issues related to energy consumption and connectivity within the network in mobile wireless sensor network indulges so many researchers to find out the optimal solutions. This paper presents a new probabilistic algorithm to analyze the network connectivity by taking in account the parameters like network probability, detection area, radius of the individual nodes and whole detection area etc. The targated area is taken for free space propagation. This methodology ensures the network connectivity, sustainability of communication and optimizes the energy consumption at utmost level. The probability theory has been used to find out a feasible mathematical network model. In this model the variation of sensor nodes with respect to the detection area has been observed and analyzed. Also, the relationship between communication radius, sensor nodes deployed, and detection area has been identified. A new algorithm is also proposed to optimize energy and maintain the connectivity by increasing the connectivity factor. Also the simulation graph of the proposed model is presented to validate the mathematical network model.

Energy-efficient and fault-tolerant drone-BS placement in heterogeneous wireless sensor networks

This paper introduces a distributed and energy-aware algorithm, called Minimum Drone Placement (MDP) algorithm, to determine the minimum number of base stations mounted on resource-rich Unmanned Aerial Vehicles (UAV-BS), commonly referred to as drone-BS, and their possible locations to provide fault tolerance with high network connectivity in heterogeneous wireless sensor networks. This heterogeneous model consists of resource-rich UAV-BSs, acting as gateways of data, as well as ordinary sensor nodes that are supposed to be connected to the UAV-BSs via multi-hop paths. Previous efforts on fault tolerance in heterogeneous wireless sensor networks attempt to determine transmission radii of the sensor nodes based on the already deployed base station positions. They assume that the base stations are stationary and arbitrarily deployed regardless of the position of the sensor nodes. Our proposed MDP algorithm takes into account the desired degree of fault tolerance and the position of ordinary sensor nodes to determine the optimal number of UAV-BSs and their locations. The MDP algorithm consists of two steps. In the first step, each sensor node chooses low-cost pairwise disjoint paths to a subset of candidate UAV-BSs, using an optimization based on the well-known set-packing problem. In the last step, depending on the desired degree of fault tolerance, MDP chooses a subset of these UAV-BS candidates using a novel optimization based on the well-known set-cover problem. Through extensive simulations, we demonstrate that the MDP achieves up to 40% improvement in UAV-connected lifetimes compared to a random and uniform distribution of UAV-BSs.

Energy-efficient coverage and connectivity of wireless sensor network in the framework of hybrid sensor and vehicular network

Hybrid Sensor and Vehicular Network (HSVN) merges both Vehicular Ad hoc Network (VANET) and Wireless Sensor Network (WSN) to create a framework of collaboration between the two networks. The main objective of this collaboration is to provide real-time detection of dangerous road conditions for the improvement of road safety. To create a reliable HSVN, coverage and connectivity problems of WSN represent the most fundamental issues to ensure an effective road sensing and a robust data communication in HSVN applications. In this respect, we have proposed a distributed protocol for ensuring both coverage and connectivity of WSN in the framework of HSVN. The proposed protocol ensures the detection of any event occurring on the road and the connectivity between sensor nodes even in the case of sensor node failure. Also, the energy consumption is reduced by keeping only a minimum number of sensor nodes in active state. The WSN lifetime is extended by balancing the energy consumption among all sensor nodes and by allowing the sensor nodes to serve alternatively as a gateway which is responsible for reporting any detected event to the passing vehicles. Simulation results show that the proposed protocol achieves 100% of road coverage and energy consumption is improved up to 14%. The proposed protocol is reliable in the case of sensor node failure; coverage and connectivity are improved up to 13% and 87%, respectively, in the case of 30% of failed sensor nodes. These results indicate that the proposed protocol is promising as it outperforms the existing ones.

Hybrid gravitational search algorithm based model for optimizing coverage and connectivity in wireless sensor networks

Recently, the wireless sensor networks (WSNs) found its extensive application in surveillance and target tracking. For these two WSN applications, connectivity and coverage play a major role most particularly for target tracking. A large number of available sensor nodes track targets, during which a massive redundant data gets generated, which may minimize the system performance. Most particularly during the sensor node failure, the major intention of coverage and connectivity optimization model is to select less number of sensor nodes with maximum direct sensor node connectivity. But existing algorithms fail to achieve minimal node selection, therefore to mitigate the barriers of the traditional coverage algorithms, this paper proposed the hybrid Gravitational Search algorithm with social ski-driver (GSA-SSD) based model. This hybrid approach in target based WSN optimizes the coverage and connectivity requirement. By adapting the dynamic behaviour of SSD algorithm, the performance of GSA gets improved. Finally, the relative performance of the proposed hybrid GSA-SSD based optimization model is validated and compared with other optimization algorithms. On the basis of uncovered area rate and a number of sensor nodes the performance is evaluated. The results are implemented in the MATLAB simulation tool. Further, the performance enhancement in terms of uncovered area rate, number of selected active sensors, energy consumption, connectivity and network lifetime is achieved with randomly deployed nodes.

Disjoint connectivity of wireless sensor network

AbstractGrowing ramification in WSN contemplations are not restricted to routing, construction of protocols, dynamic of mobile nodes and infrastructure of the network. Although transcended to geometric level demonstrated as computational and dynamical geometries in spite of graph theory. In this paper we present step forward recognition features of a network devoted to solve the problem of reconstructing the disconnected network by connecting any disconnected chains. It considers geometrical properties of random depletion nodes deviated from unit grid. Number of chains and number of nodes in each chain are calculated with the average number of connections to a total nodes and longest chain. Histogram represented number of chains and numbers of nodes for each chain are used to show fragmentation of the network. Algorithm included a method to translate adjacent matrix to chain matrix and vice versa to check the agreement of initial case with the results. The amount of chain deviation and average connections per node for longest connected chain and for the total network are drawn as bar charts and conduct interpretations.

Long Range Backhaul Microwave Connectivity in Wireless Sensor Networks via a New Antenna Designed for ISM 2.4 GHz Band

This study aimed to explore a metallic striped grid array planar antenna, analyze it numerically in terms of its parameters, and optimize it for best performance. It may be an appropriate candidate for long-range point-to-point connectivity in wireless sensor networks. Antenna gain and frequency impedance bandwidth are two important performance parameters. For an efficient antenna, its gain should be high while maintaining operating bandwidth wide enough to accommodate the entire frequency range for which it has been designed. Concurrently, antenna size should also be small. In this study, antenna dimensions were kept as small as possible without compromising its performance. Its dimensions were 300 mm × 210 mm × 9.9 mm, which made it compact and miniature. It had a maximum gain of 16.72 dB at 2.45 GHz and maximum frequency impedance bandwidth of 7.68% relative to 50 Ω. It operated across a frequency band ranging from 2.38 GHz to 2.57 GHz, encapsulating the entire ISM 2.4 GHz band. Its radiation efficiency remained above 93% in this band with a maximum of 98.5% at 2.45 GHz. Moreover, it also had narrow HPBWs in horizontal and vertical planes having values of 18.52° and 31.25°, respectively.

VANET: A novel service for predicting and disseminating vehicle traffic information

SummaryThe arrival of cloud computing technology promises innovative solutions to the problems inherent in existing vehicular ad hoc network (VANET) networks. Because of the highly dynamic nature of these networks in crowded conditions, some network performance improvements are needed to anticipate and disseminate reliable traffic information. Although several approaches have been proposed for the dissemination of data in the vehicular clouds, these approaches rely on the dissemination of data from conventional clouds to vehicles, or vice versa. However, anticipating and delivering data, in a proactive way, based on query message or an event driven has not been defined so far by these approaches. Therefore, in this paper, a VANET‐Cloud layer is proposed for traffic management and network performance improvements during congested conditions. For the traffic management, the proposed layer integrates the benefits of the connected sensor network (CSN) to collect traffic data and the cloud infrastructure to provide on‐demand and automatic cloud services. In this work, traffic services use a data exchange mechanism to propagate the predicted data using a fuzzy aggregation technique. In the evaluation phase, simulation results demonstrate the effectiveness of the proposed VANET‐Cloud layer to dramatically improve traffic safety and network performance as compared with recent works.

Event-Triggered Task-Switching Control Based on Distributed Estimation

This paper studies how to control an agent in an uncertain environment over a connected sensor network, such that the agent is able to finish a sequence of tasks, namely, reaching certain sets in order. Based on multiple offline reference trajectories and constrained communication between the agent and the sensor network, an event-triggered task-switching control framework is proposed, so that the agent state remains in each task set for the desired time and then switches to the next task. Employing a local predicted control law and the messages from neighboring sensors, a two time-scale distributed filter is proposed for each sensor to estimate the agent state. Under mild system conditions (i.e., stabilization and collective detectability), the estimation error and trajectory tracking error are shown to be asymptotically upper bounded.

Resilient and secure wireless sensor network under non-full visibility

Connectivity, resilient and unsplittability are the essential requirements of any wireless sensor network (WSN). Connectivity ensures that the complete network is a single component and there exists at least one path between any two nodes, while resilient and unsplittability ensures that the network remains connected even if a linear proportion of the nodes were compromised by the adversary. In this work we consider a wireless sensor network induced by kryptograph with non-full visibility condition. We derive a threshold for transmission range above which the WSN becomes connected almost surely. We also derive threshold conditions to show resilience and unsplittability of connected sensor networks in an almost sure sense and provided simulated experiments in support of our claims.