Multi-hop Wireless Sensor Networks Research Articles

An Unequal Clustering and Multi-Hop Routing Protocol Based on Fuzzy Logic and Q-Learning in WSNs

Clustering-based routing techniques are key to significantly extending the lifetime of wireless sensor networks (WSNs). However, these approaches often do not address the common hotspot issue in multi-hop WSNs. To overcome this challenge and enhance network lifespan, this study presents FQ-UCR, a hybrid approach that merges unequal clustering based on fuzzy logic (FL) with routing optimized through Q-learning. In FQ-UCR, a tentative CH employs a fuzzy inference system (FIS) to compute its probability of being selected as the final CH. By using the Q-learning algorithm, the best forwarding cluster head (CH) is chosen to construct the data transmission route between the CHs and the base station (BS). The approach is extensively evaluated and compared with protocols like EEUC and CHEF. Simulation results demonstrate that FQ-UCR improves energy efficiency across all nodes, significantly extends network lifetime, and effectively alleviates the hotspot issue.

An Adaptive Procedure of Time Synchronization in Unstructured Multi-Hop Wireless Sensor Networks using Butterfly Optimization Algorithm

Abstract Wireless sensor networks (WSNs) play a pivotal role in various applications, ranging from environmental monitoring to defence technology. This paper proposes a novel time synchronization protocol for WSNs inspired by the Butterfly Optimization algorithm. The time synchronization problem is formulated into an optimization problem for heuristic evolutionary algorithms, and the recently reported Butterfly optimization algorithm is used to optimize clock parameters and carry out global network synchronization. A working protocol is proposed for clock synchronization in multi hop WSN. The proposed protocol is evaluated experimentally against the Newton inspired Time Synchronization protocol and the Average Proportional Integral Synchronization protocol. Experimental results showed better performance in terms of synchronization accuracy as compared to the other protocols.

Fault detection in single-hop and multi-hop wireless sensor networks using a deep learning algorithm

<p>The wireless sensor network (WSN) has received significant recognition for its positive impact on environmental monitoring, yet its reliability remains prone to faults. Common factors contributing to faults include connectivity loss from malfunctioning node interfaces, disruptions caused by obstacles, and increased packet loss due to noise or congestion. This research employs a variety of machine learning and deep learning techniques to identify and address these faults, aiming to enhance the overall lifespan and scalability of the WSN. Classification models such as support vector machine (SVM), gradient boosting clasifer (GBC), K-nearest neighbours (KNN), random forest, and decision tree were employed in model training, with the decision tree emerging as the most accurate at 90.23%. Additionally, a deep learning approach, the recurrent neural network (RNN), effectively identified faults in sensor nodes, achieving an accuracy of 93.19%.</p>

Achieving Reliability of Privacy-preserving Phantom Routing Protocols in Multi-hop Wireless Sensor Networks

Due to the open nature of wireless channels and sensor node resource constraints, it is challenging to secure the communication in wireless sensor networks (WSNs) while simultaneously protecting the privacy of node location data. Therefore, a significant amount of research focusing on source location privacy (SLP) protocols has been conducted. The amount of research on SLP reliability, meanwhile, is insignificant. This study explores the operational features of various privacy-preserving phantom routing protocols and simulates WSNs with varied network configurations to investigate how different routing strategies affect SLP reliability. Safety period and capture ratio metrics are used to compute SLP reliability. Simulation results show that integration of phantom routing with fake packet distribution mechanisms adversely impacts SLP reliability. SLP reliability decreases also as the number of fake packet sources increases. Research proves that a protocol with many fake packet sources achieves SLP reliability for a mission duration of 940 rounds, while a protocol with no fake packet sources achieves SLP reliability for 1658 rounds.

Software-Defined Networking-Enabled Efficient Default Route Configuration in IEEE 802.15.4 Protocol: A Smart Algorithmic Approach

Today’s software-defined networking (SDN) applications have many challenges. Its main applications are focused on networks with nodes with high processing capacity. Applying SDN technology in nodes operating on batteries with limited computing capabilities is challenging. In this context, this paper proposes SDN-enabled algorithms for the remote configuration of the default route to be applied in multi-hop wireless sensor networks (WSNs) with tree-type topology using the IEEE 802.15.4 protocol. The routing algorithm to define the default route of each node is executed in an SDN-enabled WSN controller (SDWSN). The SDWSN controller receives information on the state of the network, executes the Djikstra or Kruskal algorithms, and configures the default route of the nodes remotely. The best route selection is based on the battery level of the nodes and the distance between them. The results show that using network protocols to configure the nodes remotely is unnecessary.

A comparative analysis on Relibale routing models in wireless sensor in smart applications

Researchers are drawn to Wireless Sensor Networks (WSNs) due to its versatility and possible use cases in a variety of fields, including target tracking and identification environmental sensing, industrial process tracking, and tactical systems. Recently, there has been a lot of focus on the particular issues that arise from implementing routing in sensor networks as opposed to the more conventional data routing in wireless connections. Due to the importance of energy conservation in the design of WSNs, numerous protocols for routing, power management, and data transmission have been developed for these networks. When it comes to environmental monitoring, traffic monitoring, etc., routing in WSNs is crucial. The primary objective of this study is to analyse routing issues and to analyse routing-related optimization issues. Features pertaining to routing issues like energy consumption, security, speed, and dependability are explored later. Attention has been paid to the routing protocols, which might vary by use case and network design. In this study, a comprehensive review is performed on the cutting-edge approaches to routing in WSNs. A brief introduction to WSNs and a discussion of the obstacles that routing protocols must overcome throughout their creation before moving on to a thorough examination of the various routing approaches now in use is considered. The comparative analysis is performed different routing techniques like Energy-Aware Routing for Software-Defined Multihop Wireless Sensor Networks (EAR-SDMWSN), DORA: A Destination-Oriented Routing Algorithm for Energy-Balanced Wireless Sensor Networks (DORA) and Energy Proficient Load Balancing Routing Scheme for Wireless Sensor Networks (EP-LBR). The benefits and drawbacks of each routing method, with an emphasis on performance is also performed.

RDSM: Underwater multi-AUV relay deployment and selection mechanism in 3D space

Underwater Wireless Sensor Networks (UWSNs) are widely used in naval military field and marine resource exploration. However, challenges such as resource inefficiency and unbalanced energy consumption severely hinder their practical applications. In this paper, we establish a model of underwater multi-hop wireless sensor network with multiple AUVs as relay nodes, which describes the data transmission process within the network. Based on this, an underwater multi-AUV Relay Deployment and Selection Mechanism in 3D space (RDSM) is proposed to achieve efficient underwater networking. Specifically, the RDSM includes the following key components. Firstly, an optimized relay node deployment strategy (RNDS) is used to deploy AUV nodes to effectively ensure network connectivity. Compared with traditional methods, this strategy has unique advantages in considering underwater space characteristics and can better adapt to the complex underwater environment. Secondly, a new utility function is constructed by integrating factors such as throughput, energy consumption, and load. The relay selection strategy based on utility maximization (RSS-UM) is used to select the next-hop relay node. This strategy is innovative in improving relay selection efficiency and optimizing network performance. Finally, in response to the problem of rapid energy consumption of relay nodes close to the base station, a power adjustment scheme is introduced to achieve a balance in node energy consumption, which is of great significance for prolonging network lifetime and improving overall stability. Experimental results show that compared with existing methods, the proposed mechanism achieves high utility and throughput, while maintaining balanced node energy consumption.

Adaptive squirrel coyote optimization-based secured energy efficient routing technique for large scale WSN with multiple sink nodes

In general, Wireless Sensor Networks (WSNs) require secure routing approaches for delivering the data packets to their sinks or destinations. Most of the WSNs identify particular events in their explicit platforms. However, several WSNs may examine multiple events using numerous sensors in a similar place. Multi-sink and multi-hop WSNs include the ability to offer network efficiency by securing effective data exchanges. The group of nodes in the multi-sink scenario is described through a distance vector. Though, the efficiency of multi-sink WSNs is considerably impacted by the routing of data packets and sink node placement in the cluster. In addition, many WSNs for diverse reasons existed in the similar geographical region. Hence, in this task, a secured energy-efficient routing technique is designed for a Wireless sensor network with Large-scale and multiple sink nodes. Here, the concept of an improved meta-heuristic algorithm termed Adaptive Squirrel Coyote Search Optimization (ASCSO) is implemented for selecting the accurate selection of cluster head. The fitness function regarding residual distance, security risk, energy, delay, trust, and Quality of Service (QoS) is used for rating the optimal solutions. The consumption of energy can be reduced by measuring the mean length along with the cluster head and multiple sink nodes. The latest two heuristic algorithms such as Coyote Optimization Algorithm (COA) and Squirrel Search Algorithm (SSA) are integrated for suggesting a new hybrid heuristic technique. Finally, the offered work is validated and evaluated by comparing it with several optimization algorithms regarding different evaluation metrics between the sensor and sink node.

Novel DV-hop algorithm-based machines learning technics for node localization in rang-free wireless sensor networks

Localization is a critical concern in many wireless sensor network (WSN) applications. Furthermore, correct information regarding the geographic placements of nodes (sensors) is critical for making the collected data valuable and relevant. Because of their benefits, such as simplicity and acceptable accuracy, the based connectivity algorithms attempt to localize multi-hop WSN. However, due to environmental factors, the precision of localisation may be rather low. This publication describes an Extreme Learning Machine (ELM) technique for minimizing localization error in range-free WSN. In this paper, we propose a Cascade Extreme Learning Machine (Cascade-ELM) to increase localization accuracy in Range-Free WSNs. We tested the proposed approaches in a variety of multi-hop WSN scenarios. Our research focused on an isotropic and irregular environment. The simulation results show that the proposed Cascade-ELM algorithm considerably improves localization accuracy when compared to previous algorithms derived from smart computing approaches. When compared to previous work, isotropic environments show improved localization results.

ACC-LDPC and ACC-RS/LDPC Schemes for Reliable and Energy-Efficient Multi-hop Wireless Sensor Network

ACC-LDPC and ACC-RS/LDPC Schemes for Reliable and Energy-Efficient Multi-hop Wireless Sensor Network

MCSO-MW: An Energy Optimized Data Switching Scheme for Multi-hop Wireless Sensor Networks

Due to continuous growth in the field of wireless sensor networks (WSN), it holds enormous growth in the multidisciplinary domains to provide a promising solution. Especially, on the internet of things (IoT) based edge device network, WSN plays a significant area in the field of data collection and physical entity monitoring. The effectiveness of the routing scheme in WSN can be directly measured through the amount of data transmission, network topology, intermediate hop counts, and data transmission distance. Similarly, an ideal energy model can improve the entire system’s performance and sustainability over successive data transmission. In this paper, a multi-objective chicken swarm optimization (CSO) algorithm is adopted to optimize energy consumption over WSN and improve the system performance through an effective routing approach. Furthermore, the proposed approach is adopted to partition the entire sensor network into multiple clusters and select the partitioned head among the sensor nodes. The competence of the proposed approach is validated against other existing approaches.

Multiway Relay Based Framework for Network Coding in Multi-Hop WSNs

In today’s information technology (IT) world, the multi-hop wireless sensor networks (MHWSNs) are considered the building block for the Internet of Things (IoT) enabled communication systems for controlling everyday tasks of organizations and industry to provide quality of service (QoS) in a stipulated time slot to end-user over the Internet. Smart city (SC) is an example of one such application which can automate a group of civil services like automatic control of traffic lights, weather prediction, surveillance, etc., in our daily life. These IoT-based networks with multi-hop communication and multiple sink nodes provide efficient communication in terms of performance parameters such as throughput, energy efficiency, and end-to-end delay, wherein low latency is considered a challenging issue in next-generation networks (NGN). This paper introduces a single and parallels stable server queuing model with a multi-class of packets and native and coded packet flow to illustrate the simple chain topology and complex multiway relay (MWR) node with specific neighbor topology. Further, for improving data transmission capacity in MHWSNs, an analytical framework for packet transmission using network coding at the MWR node in the network layer with opportunistic listening is performed by considering bi-directional network flow at the MWR node. Finally, the accuracy of the proposed multi-server multi-class queuing model is evaluated with and without network coding at the network layer by transmitting data packets. The results of the proposed analytical framework are validated and proved effective by comparing these analytical results to simulation results.

Multi-Access Edge Computing assisted ultra-low energy scheduling and harvesting in multi-hop Wireless Sensor and Actuator Network for energy neutral self-sustainable Next-gen Cyber-Physical System

Energy Neutrality is the need of the hour for future Cyber-physical infrastructure. Many past research works suggest low duty cycle networking for energy-efficient wireless sensor network; however, research problem still persist as these proposals have some practical deployment bottlenecks like sleep-latency and may trade-off with data-fidelity and Quality-of-Service (QoS) parameters. The research objective of this work is to propose a novel design for wireless sensor–actuator mote system to minimize energy consumption and compensate with harvesting to achieve energy neutral operation in multi-hop Wireless Sensor and Actuator Network (WSAN); A network scenario that is much needed for Internet of Thing (IoT) applications in future ready Next-gen Cyber Physical System (NG-CPS). In this paper, we have proposed a novel state-of-the-art Multi-Access/Mobile Edge Computing (MEC) assisted Low-Duty-Cycle Scheduling of Trans-Receiver for Store-Process-Then-Forward (LDCS-TR-SPTF) scheme in multi-hop WSAN for reducing the overall energy consumption. In addition to energy conservation, we have also proposed a hybrid harvesting to compensate energy to achieve energy neutral self-sustainable NG-CPS. The proposed novel LDCS-TR-SPTF has been implemented on multiple custom-made sensor–actuator motes equipped with ARM-based System-on-Chip (SoC) and IEEE 802.11 network interface. These motes are working both as end-nodes and relay nodes in a multi-hop WSAN testbed scenario for testing and validation of our proposed scheme. The results are promising with an overall energy conservation of 49.1% using our novel LDCS-TR-SPTF in comparison to stock IEEE 802.11. We have implemented solar energy harvester on wireless sensor–actuator motes to compensate the reduced energy consumption and achieved complete energy-neutrality. Motes are completely energy-autonomous in multi-hop WSAN scenario by eliminating the need of access to external power-grid for future cyber–physical system.

Improved Wireless Sensor Network Localization Algorithm Based on Selective Opposition Class Topper Optimization (SOCTO)

One of the most important challenges in wireless sensor networks is the issue of localization. Furthermore, it is critical to monitor and evaluate the data gathered. With the aid of a collection of constructed nodes known as beacons, the localization technique can measure node location. For a variety of factors, such as upkeep, lifespan, and breakdown, the fixed density of these beacons may be increased or decreased. Because of its robustness, flexibility, and economic viability, a well-known technique for locating wireless sensor network nodes is the distance vector-hop (DV-Hop) algorithm. As a result, researchers continue to look for ways to develop it. Based on a proposed selective opposition class topper optimization (SOCTO), an enhanced DV-Hop localization algorithm is developed. It also focuses on an optimised formulation to compute the average hop-size with weight of beacon nodes in order to reduce the localization error within the estimated distance between the beacon and the dumb node, due to improved localization accuracy. The range-free localization algorithm in uniform multi-hop wireless sensor networks is the subject of a recent study. The results show that our proposed method outperforms the DV-Hop technique and related techniques in terms of average localization error (\(0.05\%\)) versus random beacon node deployment, average localization error (\(0.04\%\)) versus circular beacon node deployment, and average localization error (\(0.08\%\)) versus spiral beacon node deployment.

Decision fusion for multi-route and multi-hop Wireless Sensor Networks over the Binary Symmetric Channel

The decision fusion for multi-route and multi-hop Wireless Sensor Networks (WSNs) is studied, wherein a discrete memoryless channel model, i.e., the Binary Symmetric Channel (BSC), is considered to characterize the relay transmission of each hop from the local sensor to the fusion center. In particular, we first develop the optimal log-likelihood ratio (LLR) based decision fusion rule, wherein the fusion center is assumed to have perfect knowledge of both the local sensor performance indices and the Channel State Information (CSI), i.e., crossover probability for each BSC. Secondly, we derive the suboptimum and robust fusion rules for two cases. In the first case, channel condition from the source to the local sensor is considered to be ideal. In the second case, the crossover probability for each BSC is assumed to be relatively large or small. Our result show that our suboptimum fusion detectors require less or no a priori information about crossover probability and/or the local sensor performance indices, and thus are easy to implement. We also show that the simple decision fusion statistic, i.e., the counting-based statistic, can be directly derived from the optimal LLR-based statistic for both cases. These suboptimum fusion rules are clearly desired for applications, wherein perfect estimation of the local sensor performance and CSI is complexity-intensive or unachievable. Furthermore, the optimal LLR-based scheme for joint decision fusion and CSI estimation is proposed. We uniformly quantize the equivalent crossover probability into discrete status, and thus give a suboptimum but more computationally practical scheme. The performance evaluation is finally developed both analytically and through simulation.

Energy-Efficient Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

We study a heterogeneous wireless sensor network (WSN) where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> heterogeneous access points (APs) gather data from densely deployed sensors and transmit their sensed information to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> heterogeneous fusion centers (FCs) via multi-hop wireless communication. The heterogeneous optimal deployment of APs and FCs is modeled as an optimization problem with total wireless communication power consumption of the network as its objective function. We consider both static WSNs, where APs and FCs retain their deployed position, and mobile WSNs where APs and FCs can move from their initial deployment to their optimal locations. Based on the derived necessary conditions for the optimal deployment in static WSNs, we propose an iterative algorithm to deploy APs and FCs. In addition, we study the necessary conditions of the optimal movement-efficient deployment in mobile WSNs with constrained movement energy and present iterative algorithms to find such deployments, accordingly. Simulation results show that our proposed deployment algorithms outperform the existing methods in the literature, and achieve a lower total wireless communication power in both static and mobile WSNs.

Retraction Note to: Energy Efficient Cluster based Multilevel Hierarchical Routing for multi-hop Wireless Sensor Network

Retraction Note to: Energy Efficient Cluster based Multilevel Hierarchical Routing for multi-hop Wireless Sensor Network

Retraction Note to: A provenance based defensive technique to determine malevolent selective forwarding attacks in multi-hop wireless sensor networks

Retraction Note to: A provenance based defensive technique to determine malevolent selective forwarding attacks in multi-hop wireless sensor networks

Design of Remote Real-Time Monitoring and Control Management System for Smart Home Equipment Based on Wireless Multihop Sensor Network

With the intensification of the pace of modern urban life and the increase of work pressure, people have higher requirements for the safety and comfort of home. However, the rapid development of Internet of Things technology, wireless communication technology, embedded technology, and data fusion technology has made this desire possible, thus making intelligent and safe. Using wireless sensor network, intelligent home system can realize the real-time collection of object location and state information, remote operation of home equipment, as well as the monitoring of the information of personnel activities, etc. However, how to efficiently analyze and integrate these information to be applied to the intelligent home system is one of the problems that need to be solved; further study of the smart home system of personal behavior identifies fire monitoring and remote monitoring of mining applications. Such information collection and integration of technology and method are given based on wireless sensor network transfer of key technologies; intelligent home security monitoring system based on Bayesian networks is proposed and a card. According to the theoretical fire monitoring method, and based on the Bayesian belief network personal behavior identification model, this paper provides the theory and method for the remote safety monitoring and control in the intelligent home environment. In this paper, based on the multisensor data fusion of smart home security, real-time monitoring alarm platform is built. Through the multisensor detection module for the home fire gas human infrared monitoring, the detected data is transmitted to the data fusion center for processing; processed results are uploaded to the cloud through the Internet. When abnormal conditions occur, users can log in to the mobile phone client to view abnormal alarm results.

Long-Range Low-Power Multi-Hop Wireless Sensor Network for Monitoring the Vibration Response of Long-Span Bridges.

Recently, vibration-based monitoring technologies have become extremely popular, providing effective tools to assess the health condition and evaluate the structural integrity of civil structures and infrastructures in real-time. In this context, battery-operated wireless sensors allow us to stop using wired sensor networks, providing easy installation processes and low maintenance costs. Nevertheless, wireless transmission of high-rate data such as structural vibration consumes considerable power. Consequently, these wireless networks demand frequent battery replacement, which is problematic for large structures with poor accessibility, such as long-span bridges. This work proposes a low-power multi-hop wireless sensor network suitable for monitoring large-sized civil infrastructures to handle this problem. The proposed network employs low-power wireless devices that act in the sub-GHz band, permitting long-distance data transmission and communication surpassing 1 km. Data collection over vast areas is accomplished via multi-hop communication, in which the sensor data are acquired and re-transmitted by neighboring sensors. The communication and transmission times are synchronized, and time-division communication is executed, which depends on the wireless devices to sleep when the connection is not necessary to consume less power. An experimental field test is performed to evaluate the reliability and accuracy of the designed wireless sensor network to collect and capture the acceleration response of the long-span Manhattan Bridge. Thanks to the high-quality monitoring data collected with the developed low-power wireless sensor network, the natural frequencies and mode shapes were robustly recognized. The monitoring tests also showed the benefits of the presented wireless sensor system concerning the installation and measuring operations.