Linear Wireless Sensor Networks Research Articles

Evaluation of Green Strategies for Prolonging the Lifespan of Linear Wireless Sensor Networks.

Battery-powered sensor nodes encounter substantial energy constraints, especially in linear wireless sensor network (LWSN) applications like border surveillance and road, bridge, railway, powerline, and pipeline monitoring, where inaccessible locations exacerbate battery replacement challenges. Addressing these issues is crucial for extending a network's lifetime and reducing operational costs. This paper presents a comprehensive analysis of the factors affecting WSN energy consumption at the node and network levels, alongside effective energy management strategies for prolonging the WSN's lifetime. By categorizing existing strategies into node energy reduction, network energy balancing, and energy replenishment, this study assesses their effectiveness when implemented in LWSN applications, providing valuable insights to assist engineers during the design of green and energy-efficient LWSN monitoring systems.

Self-Organizing and Routing Approach for Condition Monitoring of Railway Tunnels Based on Linear Wireless Sensor Network.

Real-time status monitoring is crucial in ensuring the safety of railway tunnel traffic. The primary monitoring method currently involves deploying sensors to form a Wireless Sensor Network (WSN). Due to the linear characteristics of railway tunnels, the resulting sensor networks usually have a linear topology known as a thick Linear Wireless Sensor Network (LWSN). In practice, sensors are deployed randomly within the area, and to balance the energy consumption among nodes and extend the network's lifespan, this paper proposes a self-organizing network and routing method based on thick LWSNs. This method can discover the topology, form the network from randomly deployed sensor nodes, establish adjacency relationships, and automatically form clusters using a timing mechanism. In the routing, considering the cluster heads' load, residual energy, and the distance to the sink node, the optimal next-hop cluster head is selected to minimize energy disparity among nodes. Simulation experiments demonstrate that this method has significant advantages in balancing network energy and extending network lifespan for LWSNs.

Finite-horizon energy allocation scheme in energy harvesting-based linear wireless sensor network

Linear wireless sensor networks (LWSNs) are a specialized topology of wireless sensor networks (WSNs) widely used for environmental monitoring. Traditional WSNs rely on batteries for energy supply, limiting their performance due to battery capacity constraints, while renewable energy harvesting technology is an effective approach to alleviating the battery capacity bottleneck. However, the stochastic nature of renewable energy makes designing an efficient energy management scheme for network performance improvement a compelling research problem. In this paper, we investigate the problem of maximizing throughput over a finite-horizon time period for an energy harvesting-based linear wireless sensor network (EH-LWSN). The solution to the original problem is very complex, and this complexity mainly arises from two factors. First, the optimal energy allocation scheme has temporal coupling, i.e., the current optimal strategy relies on the energy harvested in the future. Second, the optimal energy allocation scheme has spatial coupling, i.e., the current optimal strategy of any node relies on the available energy of other nodes in the network. To address these challenges, we propose an iterative energy allocation algorithm for EH-LWSN. Firstly, we theoretically prove the optimality of the algorithm and analyze the time complexity of the algorithm. Next, we design the corresponding distributed version and consider the case of estimating the energy harvest. Finally, through experiments using a real-world renewable energy dataset, the results show that the proposed algorithm outperforms the other two heuristics energy allocation schemes in terms of network throughput.

A energy efficiency optimization routing processing method for Linear Wireless Sensor Networks

Linear wireless Sensor networks (LWSNs) are extensively utilized to monitor linear infrastructure such as railways, bridges, mines, and borders. In the large-scale deployment of sensor networks, extending network life and improving network energy balance remains a significant challenge. The existing routing protocols adopt the path planning method based on the routing information database, which can effectively transmit data packets. However, the methods consume additional energy when establishing and maintaining routing tables, significantly reducing the nodes’ lifespan and leading to unstable data transmission quality. This paper proposes a dynamic random multipath routing method (DRMRM) for LWSNs. The technique combines the node depth and residual energy models to select the optimal next-hop relay node without relying on the transmission routing table. At the same time, we designed a data loss retransmission mechanism and a data loop retreat mechanism to prevent data packets from reaching a dead end. The experimental results demonstrate that our routing method is superior to existing energy consumption balance and network lifespan protocols.

Distance-Based Queuing for Scalable and Reliable Linear Wireless Sensor Networks in Smart Cities.

The reliability and scalability of Linear Wireless Sensor Networks (LWSNs) are limited by the high packet loss probabilities (PLP) experienced by the packets generated at nodes far from the sink node. This is an important limitation in Smart City applications, where timely data collection is critical for decision making. Unfortunately, previous works have not addressed this problem and have only focused on improving the network's overall performance. In this work, we propose a Distance-Based Queuing (DBQ) scheme that can be incorporated into MAC protocols for LWSNs to improve reliability and scalability without requiring extra local processing or additional signaling at the nodes. The DBQ scheme prioritizes the transmission of relay packets based on their hop distance to the sink node, ensuring that all packets experience the same PLP. To evaluate the effectiveness of our proposal, we developed an analytical model and conducted extensive discrete-event simulations. Our numerical results demonstrate that the DBQ scheme significantly improves the reliability and scalability of the network by achieving the same average PLP and throughput for all nodes, regardless of traffic intensities and network sizes.

Enhancement of the Reliability of the Linear Wireless Sensor Networks

Wireless Sensor Network (WSN) is one of the trend technologies. It was aggregation, processing, and transferring a huge amount of data in different applications that deal with the surrounding environment. Using a huge number of sensors deployed or organized in a linear configuration between two parallel lines or carvings, a specific kind of WSN is constructed to monitor a particular type of infrastructure. This type of WSN is Known as Linear Wireless Sensor Network (LWSN). LWSNs are used in monitoring applications that are arranged in linear form like underground Pipelines, Bridges, Tunnels, Railway lines, Highways, and Borderlines. A transmission process must be reliable and efficient to ensure end-to-end packet delivery. The backbone or the shortest path approach is used to improve the network performance and prolong the network lifetime. In such networks, more packets are ultimately forwarded or relayed by the sensors closest to the sink than by other types of sensors. In this paper, a backbone approach has been implemented where data is sent from the backbone and the node outside the backbone. Any node outside the backbone selects the closest backbone and sends the sensing data to it.

Development and research of reliability assessment of linear wireless sensor networks

The article is devoted to the issue of estimating the reliability of linear wireless sensor networks. Scientific research in the field of forecasting is given. This article discusses the Internet of Things (IoT) technology, which is growing by 15-20%, actively developing in all directions and its principles of operation. The area with the greatest potential for the application of the Internet of Things in Kazakhstan is smart control of resource consumption, including in the sphere of housing and communal services. Использованы методы построения и управления смарт-систем. Also describes the increase in comfort, thanks to IoT technology. User-friendly interface is used. Mainly considered the system of automation of business structures depending on the scale. All currently available methods have been suggested, which are key factors in optimizing all processes. Also considered options for modeling and system development, taking into account all the relevant problems of technology automation. The importance of the scientific topic affects the high potential for the development of IoT technology and the lack of uniform standards for devices included in these systems. The system is scalable, allowing it to be used for almost any purpose. This paper proposes an approach to solving a number of problems arising in the monitoring of long pipelines using wireless sensor networks. In order to take full advantage of the potential of IoT technologies, the architectural basis of which is formed by wireless sensor networks, it is necessary to develop tools to assess and ensure the reliability of these networks. Thus, the focus of the study is on the application-specific formalized reliability criteria for wireless sensor networks.

Criteria for the deployment of a heterogeneous linear WSN: Operability vs energy efficiency

Linear Wireless Sensor Networks (LWSN) are typically used for monitoring infrastructure systems extending over several kilometers, where propagation conditions can be inhomogeneous in different sections of the network. Obstacles and reflecting objects contribute to bit errors in data packets, which take extra time and energy to recover. However, the impact of the inhomogeneities across LWSN sections on the time and energy performance of the entire network remains underreported. In addition, conventional methods of building LWSN by distributing relay nodes among inhomogeneous sections have failed to balance operability and energy efficiency criteria. This article examines the models of time and energy loss in LWSN sections showing different signal fading, represented by the Rician K-factor in the expressions for the bit error probability. On the basis of the dependences of time losses on inter-node distances, algorithms for deploying a heterogeneous LWSN are proposed according to the criterion of minimizing end-to-end network delay without restrictions on hardware and energy resources or when distributing a limited number of nodes. As an alternative to the efficiency criterion, we propose algorithms for balancing power consumption in a heterogeneous LWSN at an acceptable level of power loss without limiting the number of nodes or at the lowest level of power loss with a limit on the number of nodes. Experiments were carried out on CC2500 TI node transceivers in five inhomogeneous LWSN sections, where K-factor ranges from 5 to 100, in order to demonstrate the efficiency of the proposed algorithms. Results showed that the end-to-end delay and energy loss can be reduced by 1.36 and 2.4 times, respectively, compared to those in networks with uniformly distributed nodes. To further assess the operability and energy efficiency of the algorithms, a scheme is proposed based on the ratio of normalized concessions in the Pareto region. Additionally, the optimal number of nodes is determined when selecting a rational algorithm for deploying a heterogeneous LWSN.

A practical method for connectivity and coverage reliability analysis for linear wireless sensor networks

Linear Wireless Sensor Networks (LWSNs) are the most suitable wireless sensor networks (WSNs) for monitoring the condition of infrastructures with linear typologies, e.g., railways, gas, or oil pipelines. Reliability of LWSNs is crucial for such applications due to their safety–critical or mission-critical nature. To this end, LWSNs of different designs need to be compared in terms of reliability to ascertain high-cost performance. Connectivity and coverage are fundamental metrics used to measure the reliability of LWSNs. However, to the best of our knowledge, there are no proper methods or tools to evaluate the reliability of LWSNs concurrently in terms of connectivity and coverage. In this paper, by reducing the size of system state space depending on the characteristics of LWSNs, we present a practical method for concurrent reliability analysis in terms of connectivity and coverage for LWSNs based on hybrid models of binary decision diagrams and divide-and-conquer schemes. The proposed method can be used to assess various LWSNs, e.g., networks with one or two sink nodes, as well as flat-based or cluster-based networks. Moreover, transmission and coverage ranges can be assigned to sensor nodes using this method. Case studies are presented to substantiate the viability of the proposed model, and some beneficial results are deduced, which can be considered to serve as basic principles for LWSN-design to ensure high-cost performance.

Reliability Comparison Between Plain-Based and Cluster-Based Linear Wireless Sensor Networks

Linear wireless sensor networks (LWSNs) are special WSNs for condition monitoring of infrastructures whose typologies are linear such as railways, gas, or oil pipelines. The reliability of LWSNs is crucial for such applications due to their safety-critical or mission-critical nature. To improve reliability, people propose cluster-based LWSNs in which, besides sensor nodes and sink nodes, some particular nodes called backbone nodes that can relay packets are adopted. The cluster-based LWSNs, which provide alternative paths for all sensor nodes, seem more reliable than plain-based LWSNs. However, the reliability analyses of plain-based and cluster-based LWSNs have yet to be studied together. In this article, we propose a hybrid model and algorithms based on decision trees to assess the connectivity reliability of both plain-based and cluster-based LWSNs. The reliability comparison of them is performed, and some interesting results are deduced, such as the cluster-based LWSN is only sometimes more reliable than a plain-based LWSN with a maximum jump factor (MJF) = 2. The result can be used as fundamental principles of LWSN design for high-cost performance.

GENERALIZATION OF THE POSITION-GENERATING MATHEMATICAL MODEL IN LINEAR WIRELESS SENSOR NETWORKS

The Linear Wireless Sensor Networks (LWSN) are a collection of wireless sensors arranged in a linear fashion. In order to allow them a better organization, several topologies have been proposed in the research. One of the most recent of them assumes a topology called redundant k-variant in which the redundancy factor k is a variable. This topology is based on a model generating the Euclidean positions of the nodes in an increasing way, the topology divides the network into two groups of nodes with different redundancy factors. This topology model increases the availability of the network especially in the areas close to the sink, compared to other topological models in which the redundancy factor was fixed for all the nodes of the network.In this paper we propose a generalization of the mathematical model proposed in the redundant k-variant model by generalizing the variation of the redundancy factor for all the nodes of the network and thus eliminating the fixed nature of the redundancy factor within the groups of nodes in the network in the k-variant model.In the approach proposed in this paper, the redundancy factor varies as one moves away from the sink. In this model, we choose, for each node, the best position among all possible ones. We use a system based on an arithmetic sequence to define an equation whose solution will generate the positions of the different nodes. We have also defined a specific resolution method coded in Python to choose the right values from all the solutions.The simulations focused on four series of transmissions based on different topologies. The experiments showed a much higher energy efficiency of the network in favor of the proposed model.

A Miniaturized Multi-layer Microstrip Antenna for Linear Wireless Sensor Network Monitoring Systems

This article presents a sub-GHz ISM band microstrip patch antenna based on the use of multi-layer compact structure, which overcomes the shortcomings of typical microstrip antennas such as low gain and high resonant frequency. The antenna was simulated using an electromagnetic simulator, ANSYS HFSS, and fabricated on two different substrates: RT Duroid 5880 and FR4 epoxy with a compact size of 100 x 100 x 8 mm3 (0.29λ × 0.29λ × 0.02λ). The simulated results of the antenna were then compared with the measured ones, and the two were observed to have a reasonable agreement. The proposed antenna operates in the sub-GHz license-free ISM band (862-875 MHz), with a gain value of 2.92 dB. Two prototypes of the proposed antenna were fabricated and used in a Linear Wireless Sensor Networks (LWSNs) monitoring system. Results show that the proposed antenna is a good candidate for those types of LWSNs systems.

An Approach to Environmental Monitoring in Sparse Linear Wireless Sensor Networks for Energy Conservation Using Dual Sinks

An Approach to Environmental Monitoring in Sparse Linear Wireless Sensor Networks for Energy Conservation Using Dual Sinks

Message-ferrying delay-tolerant routing in linear wireless sensor networks

Message-ferrying delay-tolerant routing in linear wireless sensor networks

Message-ferrying delay-tolerant routing in linear wireless sensor networks

Message-ferrying delay-tolerant routing in linear wireless sensor networks

Privacy preserving secure expansive aggregation with malicious node identification in linear wireless sensor networks

Privacy preserving secure expansive aggregation with malicious node identification in linear wireless sensor networks

A case study on the assessment of RF switch and splitter options for coupling of transceiver modules to bidirectional antennas employed in linear wireless sensor networks

AbstractRecently, a concept of linear wireless sensor networks (LWSNs) has attracted much attention. For such networks, one of the key challenges in sensor node design is to couple transceiver modules with bidirectional antennas placed back‐to‐back for opposite radiation. As is known, simply, this can be achieved by using well‐known coupling options like radio frequency (RF) switch or splitter. However, it is important to decide between two seemingly equally good options according to the system requirements such as RF performance, power consumption, and cost. Therefore, this study aims to comparatively assess these options from the system level point of view to find out what advantages or disadvantages either provides as per the other from widespread use of them in a LWSN‐based cathodic protection monitoring of oil and natural gas pipelines in extreme environments. Preliminary field tests are also conducted to validate the efficiency of coupling options for LWSN links. Results show that RF splitter offers low power consumption and cost whereas RF switch has advantages of low loss. Thus, it is believed that this study may provide useful insights to design bidirectional sensor links for LWSNs.

Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research has also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed at a distance from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs), which over the years have been applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along with a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrates that groups containing small number of nodes with a corresponding sink node are the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it has been discovered that the energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink node for each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This, therefore, means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of an LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

Reliable Link Level Routing Algorithm in Pipeline Monitoring Using Implicit Acknowledgements.

End-to-end reliability for Wireless Sensor Network communications is usually provided by upper stack layers. Furthermore, most of the studies have been related to star, mesh, and tree topologies. However, they rarely consider the requirements of the multi-hop linear wireless sensor networks, with thousands of nodes, which are universally used for monitoring applications. Therefore, they are characterized by long delays and high energy consumption. In this paper, we propose an energy efficient link level routing algorithm that provides end-to-end reliability into multi-hop wireless sensor networks with a linear structure. The algorithm uses implicit acknowledgement to provide reliability and connectivity with energy efficiency, low latency, and fault tolerance in linear wireless sensor networks. The proposal is validated through tests with real hardware. The energy consumption and the delay are also mathematically modeled and analyzed. The test results show that our algorithm decreases the energy consumption and minimizes the delays when compared with other proposals that also apply the explicit knowledge technique and routing protocols with explicit confirmations, maintaining the same characteristics in terms of reliability and connectivity.

Performance Evaluation of Empirical Path Loss Models for a Linear Wireless Sensor Network Deployment in Suburban and Rural Environments

This article presents a preliminary propagation study on the accuracy of empirical path loss models for efficient planning and deployment of a linear wireless sensor network (LWSN) based on long range (LoRa) enabled sensor nodes in suburban and rural environments. Real-world deployment of such network requires accurate path loss modelling to estimate the network coverage and performance. Although several models have been studied in the literature to predict the path loss for LoRa links, the assessment of empirical path loss models within the context of low-height peer to peer configured system has not been provided yet. Therefore, this study aims at providing a performance evaluation of well-known empirical path loss models including the Log-distance, Okumura, Hata, and COST-231 Hata model in a peer to peer configured system where the sensor nodes are deployed at the same low heights. To this end, firstly, measurement campaigns are carried out in suburban and rural environments by utilizing LoRa enabled sensor nodes operating at 868 MHz band. The measured received signal strength values are then compared with the predicted values to assess the prediction accuracy of the models. The results achieved from this study show that the Okumura model has higher accuracy.