Wireless Sensor Network Topology Research Articles

Mechanical Vibration Test Based on the Wireless Vibration Monitoring System

In order to apply wireless sensor networks to mechanical vibration monitoring, the author proposes a wireless network topology with multiple data collection points for mechanical vibration monitoring. This structure reduces the transmission load of the data collection point, increases the data transmission rate of the network, balances the energy dissipation in the network, and utilizes the general wireless sensor network hardware platform. The network transmission protocol and related auxiliary mechanisms are designed and implemented, and a wireless vibration monitoring test platform is constructed. The transmission performance of the network structure with multiple data collection points is evaluated through the actual test. The experimental results show that by using the wireless sensor network topology with multiple data collection points, it can meet the requirements of continuous transmission of vibration data obtained by 1 kHz sampling. Conclusion. The system performance of the wireless sensor network based on this network structure has been improved under the condition of general hardware, and the network structure of multiple data collection points shows good performance in the process of high-speed data transmission.

Fruchterman–Reingold Hexagon Empowered Node Deployment in Wireless Sensor Network Application

Internet of Things (IoT) and Big Data technologies are becoming increasingly significant parts of national defense and the military, as well as in the civilian usage. The proper deployment of large-scale wireless sensor network (WSN) provides the foundation for these advanced technologies. Based on the Fruchterman–Reingold graph layout, we propose the Fruchterman–Reingold Hexagon (FR-HEX) algorithm for the deployment of WSNs. By allocating edges of hexagonal topology to sensor nodes, the network forms hexagonal network topology. A comprehensive evaluation of 50 simulations is conducted, which utilizes three evaluation metrics: average moving distance, pair correlation diversion (PCD), and system coverage rate. The FR-HEX algorithm performs consistently, the WSN topologies are properly regulated, the PCD values are below 0.05, and the WSN system coverage rate reaches 94%. Simulations involving obstacles and failed nodes are carried out to explore the practical applicability of the FR-HEX algorithm. In general, the FR-HEX algorithm can take full advantage of sensors’ hardware capabilities in the deployment. It may be a viable option for some IoT and Big Data applications in the near future.

Multi-Hop Routing Protocols for Oil Pipeline Leak Detection Systems

In recent years, various applications have emerged requiring linear topologies of wireless sensor networks (WSN). Such topologies are used in pipeline (water/oil/gas) monitoring systems. The linear structure has a significant impact on network performance in terms of delay, throughput, and power consumption. Regarding communication efficiency, routing protocols play a critical role, considering the special requirements of linear topology and energy resources. Therefore, the challenge is to design effective routing protocols that can address the diverse requirements of the monitoring system. In this paper, we present various wireless communication technologies and existing leak detection systems. We review different routing protocols focusing on multi-hop hierarchical protocols, highlighting the limitations and design issues related to packet routing in linear pipeline leak detection networks. Additionally, we present a LoRa multi-hop model for monitoring aboveground oil pipelines. A set of model parameters are identified such as the distance between sensors. In addition, the paper determines some calculations to estimate traffic congestion and energy consumption. Several alternative model designs are investigated. The model is evaluated using different multi-hop communication scenarios, and we compare the data rate and energy to provide an energy-efficient and low-cost leak detection system.

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.

Control Mechanism of Virus Propagation in Wireless Sensor Networks Based on Analytic Hierarchy Process

The research on virus propagation process and control method in wireless sensor networks (WSNs) is one of the essential challenges of network security. This paper proposes a virus control mechanism of degree, betweenness centrality, and k-core-based analytical hierarchy process (DBC-AHP) for WSNs. According to the topology of WSNs, the virus control mechanism uses the DBC-AHP to identify the crucial nodes of the network. It uses the way of crucial nodes’ self-disconnection to suppress the spread of the virus, to improve the network security. In this paper, the effectiveness of the virus control mechanism based on the DBC-AHP is verified by comparing and analyzing the effect of four different crucial node recognition algorithms. With the research of virus control mechanisms in various network environments, it is found that the average degree of nodes, the communication radius of nodes, and the probability of virus infection can affect the inhibition effect of the virus control mechanism. Furthermore, the inhibition effect of virus control mechanisms is studied under the condition with/without MAC mechanism.

Multi-stage resource-aware congestion control algorithm in edge computing environment

Due to the uneven distribution of network resources and network, traffic, congestion is an inherent attribute of the Internet network. Network congestion will increase data transmission delay, reduce network throughput, increase the packet loss rate in the network, and even cause overall network performance degradation, which may cause large losses to users. This article aims to study multistage resource-aware congestion control algorithms based on edge computing environments. This article first compares and analyzes edge computing and traditional cloud computing. There are certain differences between edge computing technology and traditional cloud computing models. In the context of the Internet of Everything, the traditional cloud computing model also has some drawbacks. The low latency of edge computing can provide a good application experience and enhance the responsiveness of user applications. At the same time, the communication load of each network department is also reduced correspondingly, which solves the network congestion. Then, a congestion control algorithm based on cooperative paths was proposed, and the wireless sensor network topology and the limit of the congestion threshold of the wireless sensor network were introduced. Then it analyzes the problem of the MPTCP-based congestion control algorithm and analyzes the simulation results based on the energy-efficiency congestion control algorithm. The experimental results show that, compared with MPTCP, the throughput of the EECCA algorithm is increased by 52.6%, and it has better throughput performance. At the same time, the energy efficiency of the three algorithms in the simulation time is 1.1813 Mbits/J, 0.8311 Mbits/J, and 0.8021 Mbits/J, respectively. Compared with MPTCP, the energy efficiency of EECCA is increased by 47.3%, achieving the goal of energy saving.

A distributed energy-efficient opportunistic routing accompanied by timeslot allocation in wireless sensor networks

Sensed data can be forwarded only in one direction to the base station in one-dimensional queue wireless sensor networks different from mesh structure, so the network lifetime will be shortened if some continuous neighboring nodes have run out of their energy. So designing routing protocols for balancing energy consumption is a challenging problem. However, traditional and existing opportunistic routing protocols for one-dimensional queue wireless sensor network proposed so far have not yet addressed this problem to prolong the network lifetime by introducing sleep mode. In this article, we propose a distributed energy-efficient opportunistic routing algorithm accompanied by timeslot allocation by using specific network topology of one-dimensional queue wireless sensor network. In our new algorithm, clustering and routing tree construction is performed while introducing the optimal relay transmission distance achieved by using opportunistic routing principle, and at the same time, interference-free wake up time is scheduled, which may optimize energy consumption and decrease the number of various control messages as possible to prolong the network lifetime. Furthermore, this improves energy efficiency by introducing the operation mode giving up cluster head role. Simulation results show that the proposed protocol can significantly improve the network performance such as energy consumption and network connectivity, when compared with other existing protocols.

Fault-Tolerant Topology of Agricultural Wireless Sensor Networks Based on a Double Price Function

Wireless sensor networks (WSN) enable the acquisition of multisource environmental data and crop states in precision agriculture. However, the complex agricultural environment causes the WSN topology to change frequently and link connection probability is difficult to predict. In order to improve the utilization of network resources and balance the network energy consumption, this paper studies an agricultural fault-tolerant topology construction method based on the potential game and cut vertex detection. Considering the connectivity redundancy, node lifetime, and residual energy, a fault-tolerant topology algorithm for agricultural WSN based on a double price function is designed. The network is clustered according to the node location and residual energy to form a single-hop effective cluster. Based on the network cluster, the price function is constructed in order to reduce energy consumption and balance network energy efficiency. The initial transmit power set supporting inter-cluster communication is obtained by potential game theory. While preserving the game characteristics of topology, the redundant links are eliminated and the transmit power is adjusted by a cut vertex detection algorithm to realize the construction of a 2-connected cluster head network. Simulation results show that the network topology constructed by the studied algorithm can balance the energy consumption and prolong the network lifetime effectively.

A Proactive Greedy Routing Protocol Precludes Sink-Hole Formation in Wireless Sensor Networks

A tree topology is a commonly employed topology for wireless sensor networks (WSN) to connect sensors to one or more remote gateways. In many-to-one traffic, routing imposes a heavy burden on downstream nodes, as the same routes are repeatedly used for packet forwarding from one or more sensor chains. The challenge is traffic paths that ensure balanced energy consumption at sink-hole to protect sensors from fast death. This paper proposes an energy consumption pattern-aware greedy routing protocol that proactively protects many-to-one topology from the sink-hole formation. The proposed protocol, Energy Balance-Based Energy Hole Alleviation in Tree Topology (EBEHA-T), precludes energy hole formation rather than retrospectively responding to a hole detection. Updated status of variations in energy consumption patterns at the sink-hole and construction feature of joint nodes in the tree topology aids in routing decision. Performance evaluation of EBEHA-T against benchmark method RaSMaLai shows increased energy-saving across the entire network and a marked improvement in energy consumption balance in energy hole zones. This precludes energy hole formation and the consequent network partitioning, leading to improved network lifetime beyond that of the RasMaLai.

Group acknowledgement mechanism for beacon-enabled wireless sensor networks

Wireless sensor networks are network of a large number of sensor nodes used for remote applications. To the expressive growth in remote sensor networks, medium access control (MAC) works faster in wireless sensor networks. The MAC protocol has to be appropriately designed to ensure the proper operation of the sensor nodes in WSNs. This paper provides energy saving by proposing group acknowledgement MAC (GACK-MAC) for an aggregated data frame transmitted to a single destination, and reducing the overhead in IEEE 802.15.4 beacon enabled wireless sensor networks. In our proposed scheme, type of acknowledgement of each sensor node is decided by the coordinator based on traffic load of the network or number of packets present in the sensor node. We performed this by adopting the star and peer-to-peer tree topologies with a coordinator having coordination with all other member nodes. Simulations are conducted, and compared with the analytical models constructed to measure the throughput, and delay metrics. Moreover, our method enhances the battery lifetime by 35% on average, throughput of 42% at maximum, and decrease the delay by 33% for each packet in network of star topology and twice the above mentioned values for battery lifetime, throughput and reduces the delay by 49% in P2P topology of wireless sensor networks.

Reliability Analysis of Social Network Data Transmission in Wireless Sensor Network Topology

In this paper, the reliability of data transmission in social networks is thoroughly studied and analyzed using wireless sensor network topology technology. This paper, based on the introduction of sensor network reliability analysis-related technology, combined with the characteristics, and needs of the sensor network itself, focuses on the study of the reliability analysis of the sensor network under the state of perturbation scheme. Based on the idea of making full use of data changes to respond to the sensor state, this paper takes the actual monitoring data of the wireless sensor network as the research object, selects the temporal correlation and spatial correlation of the measured environmental data as the reliability index by extracting the features of the wireless sensor network data, and proposes the Evidential reasoning rule- (ER-) based wireless sensor network data reliability assessment model based on Evidential reasoning rule (ER) is proposed. The data are mined, analyzed, and quantified from the perspective of content popularity, and the interest indicators of nodes on data under content popularity are analyzed to derive stable interest quantification values. Combined with the network properties, i.e., node autoassembly community, we analyze the data dissemination characteristics of social networks in wireless sensor network topology environment and derive the upper and lower bounds of data transmission capacity under node interest-driven and its variation on network performance. Social relationships among nodes affected by social attributes are considered; in turn, the data forwarding behavior of nodes is modeled using data transmission probability and data reception probability; finally, the data forwarding process is analyzed and a closed expression for the average end-to-end transmission capacity is derived in turn.

Data Transmission Reliability Analysis of Wireless Sensor Networks for Social Network Optimization

With the rapid development of the Internet in recent years, people are using the Internet less and less frequently. People publish and obtain information through various channels on the Internet, and online social networks have become one of the most important channels. Many nodes in social networks and frequent interactions between nodes create great difficulties for privacy protection, and some of the existing studies also have problems such as cumbersome computational steps and low efficiency. In this paper, we take the complex environment of social networks as the research background and focus on the key issues of mobile wireless sensor network reliability from the mobile wireless sensor networks that apply to large-scale, simpler information, and delay tolerance. By introducing intelligent learning methods and swarm intelligence bionic optimization algorithms, we address reliability issues such as mobile wireless sensor network fault prediction methods and topology reliability assessment methods in industrial application environments, the impact of mobile path optimization of mobile wireless sensor networks on data collection efficiency and network reliability, reliable data transmission based on data fusion methods, and intelligent fault tolerance strategies for multipath routing to ensure mobile wireless sensor networks operate energy-efficiently and reliably in complex industrial application environments.

Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol

Some recent researches have shown that the energy consumption problem caused by data collection in a wireless sensor network (WSN) based on a static data collector is a main threat to the network lifetime. However, with the progress of the mobile terminal technology, the implementation of mobile data collectors (MDCs) has become more popular in large-scale WSNs, but it remains a big problem to improve the Quality of Service (QoS) criteria and minimize the energy consumption at the same time. However, most existing systems based on MDCs do not successfully strike a balance between routing energy consumption and QoS. In addition, most WSN protocols fail to maintain their impact when the network topology changes. Thus, for a dynamic WSN, it is important to support an intelligent MDC to continue data propagation despite the inevitable changes in the WSN topology. Considering all the above challenges, we propose a new intelligent MDC based on the traveling salesman problem (TSP) to determine the optimal path traveled by the MDC for energy efficiency and latency. Specifically, our proposed Mobile Data Collectors-Traveling Salesman Problem-Low Energy Adaptive Clustering Hierarchy-K-Means (MDC-TSP-LEACH-K) protocol uses K-Means and Grid clustering algorithm to decrease energy consumption in the cluster head (CH) election phase. Additionally, MDC is utilized as an intermediate between CH and the sink to further enhance the QoS of WSNs, to reduce delays while collecting data, and improve the transmission phase of the LEACH protocol.

Implementation of NLOS based FPGA for distance estimation of elderly using indoor wireless sensor networks

Location or distance estimate data for the elderly is a major drawback in wireless sensor networks (WSNs). Previous research used an Artificial Neural Network (ANN) in the indoor spaces to calculate the distance between elderly people and a unique anchor node in the ZigBee WSN. The neural network was evaluated on a “Field Programmable Gate Array (FPGA)” because it was being used in a real-world application. To training, testing, and validating the ANN, the RSSI values of anchor nodes were extracted. As a result, the MAE-estimated distance error improved. In addition, one of the issues that might affect distance estimate accuracy is the mobility of persons inside the testing phase. As a result, the proposed work aims to concentrate on NLOS circumstances to examine their impact on estimated distance. NLOS situations are most frequent indoors when several rooms within a structure are involved. Difficulties can cause Non-Line-Of-Sight (NLOS) propagation when WSNs are implemented in indoor environments. However, the proposed method overcomes the issue of selecting the nodes by combining an optimization method including PSO with an FPGA to find the smallest number of nodes with a suitable “Distance Estimation Error”. To execute the indoor wireless sensor network (WSN) topology, the system includes ZigBee technology. As a result, the FPGA implementation's complexity can be decreased and it outperforms the other existing algorithms. As can be observed, the analysis of the proposed hybridizing method based on WSN is highly effective in enhancing the elderly's well-being.

Distance Matrix and Markov Chain Based Sensor Localization in WSN

Applications based on Wireless Sensor Networks (WSN) have shown to be quite useful in monitoring a particular geographic area of interest. Relevant geometries of the surrounding environment are essential to establish a successful WSN topology. But it is literally hard because constructing a localization algorithm that tracks the exact location of Sensor Nodes (SN) in a WSN is always a challenging task. In this research paper, Distance Matrix and Markov Chain (DM-MC) model is presented as node localization technique in which Distance Matrix and Estimation Matrix are used to identify the position of the node. The method further employs a Markov Chain Model (MCM) for energy optimization and interference reduction. Experiments are performed against two well-known models, and the results demonstrate that the proposed algorithm improves performance by using less network resources when compared to the existing models. Transition probability is used in the Markova chain to sustain higher energy nodes. Finally, the proposed Distance Matrix and Markov Chain model decrease energy use by 31% and 25%, respectively, compared to the existing DV-Hop and CSA methods. The experimental results were performed against two proven models, Distance Vector-Hop Algorithm (DV-HopA) and Crow Search Algorithm (CSA), showing that the proposed DM-MC model outperforms both the existing models regarding localization accuracy and Energy Consumption (EC). These results add to the credibility of the proposed DC-MC model as a better model for employing node localization while establishing a WSN framework.

Problem solution of different sensors location in organizing a Mesh topology wireless sensor network

Problem solution of different sensors location in organizing a Mesh topology wireless sensor network

Effects of Wormhole Attack on Routing Topology

The article is devoted to investigating the effects of wormhole attack on routing topology in Wireless Sensor Networks (WSNs). Currently, WSNs are increasingly vulnerable to numerous security attacks. One of the major attacks affecting WSNs involves a wormhole attack where attackers receive packets at a single end in the network and tunnel the packets to other points in the network and are subsequently replayed in the network. The wormhole attacks can affect the routing topology by redirecting traffic. Because of the nature of WNSs, attackers can develop a wormhole for packets not destined for them due to overhearing them within the wireless network and tunneling them to colluding attackers on the opposite side of the wormhole. Mainly, wormhole attacks are hazardous to ad-hoc network routing protocols. Therefore, it is evident that routing topology suffers from various vulnerabilities and needs robust security measures. This research investigates the effects of wormhole attacks on routing topology, and a simulation is presented to depict wormhole attack effects. In addition, an analysis of whormhole simulation of packet transmission with and without attacker node using Network Simulator NS-2 environment has been carried out. A simulation conducted using NS2 determined the performance of two reactive routing protocols (AODV and DSR) using their throughput, the first and the last packet received, and the total amount of bytes received in two conditions (with and without wormhole). Findings obtained demonstrate that the performance of DSR was better compared to that of AODV. The introduction of wormhole attacks in both routing protocols significantly affected the performance.

An Invulnerability Algorithm for Wireless Sensor Network's Topology Based on Distance and Energy

An Invulnerability Algorithm for Wireless Sensor Network's Topology Based on Distance and Energy

Wireless Sensor Network Topology Theory for Data Collection and Analysis of Sports Training Human Body

This paper is based on wireless sensor network topology for sports training human data collection, and the collected data are studied and analyzed in depth. According to the application requirements of sports training, a sports training system consisting of an embedded data collection terminal, and a database server is designed using wireless sensor network technology. The hardware is designed with sensor nodes and base stations to collect athletes’ motion parameters in real time. The software is designed with node and base station control software and sports database management system to realize the receiving, storing, and analyzing of sports parameters. And the system experiments were conducted, and the experimental results show that this system meets the application requirements of sports training and provides an effective tool for scientific training decision research. The needs of designing sports training systems under wireless sensor networks are analyzed, and the system is designed and implemented. Our results confirm that the use of wireless sensor network technology in the design of the sports training system improves the system application performance by 16%. And the interactivity of the sports training system in practice has increased by 8%. All of these show that the design of the sports training system under the wireless sensor network meets the actual system application requirements and has a positive impact. The design of base station control, node control, and sports database software is implemented in the software system, which can effectively realize the collection, storage, and analysis of sports parameters. Finally, the designed wireless sensor network-based sports training system is tested, and the test results indicate that the system designed in this paper can meet the needs of sports training use.

Adaptive Monitor Placement for Near Real-time Node Failure Localisation in Wireless Sensor Networks

As sensor-based networks become more prevalent, scaling to unmanageable numbers or deployed in difficult to reach areas, real-time failure localisation is becoming essential for continued operation. Network tomography, a system and application-independent approach, has been successful in localising complex failures (i.e., observable by end-to-end global analysis) in traditional networks. Applying network tomography to wireless sensor networks (WSNs), however, is challenging. First, WSN topology changes due to environmental interactions (e.g., interference). Additionally, the selection of devices for running network monitoring processes (monitors) is an NP-hard problem. Monitors observe end-to-end in-network properties to identify failures, with their placement impacting the number of identifiable failures. Since monitoring consumes more in-node resources, it is essential to minimise their number while maintaining network tomography’s effectiveness. Unfortunately, state-of-the-art solutions solve this optimisation problem using time-consuming greedy heuristics. In this article, we propose two solutions for efficiently applying Network Tomography in WSNs: a graph compression scheme, enabling faster monitor placement by reducing the number of edges in the network, and an adaptive monitor placement algorithm for recovering the monitor placement given topology changes. The experiments show that our solution is at least 1,000× faster than the state-of-the-art approaches and efficiently copes with topology variations in large-scale WSNs.