Reliable Wireless Sensor Networks Research Articles

Research on WSN reliable ranging and positioning algorithm for forest environment

Wireless sensor network (WSN) location is a significant research area. In complex environments like forests, inaccurate signal intensity ranging is a major challenge. To address this issue, this paper presents a reliable WSN distance measurement-positioning algorithm for forest environments. The algorithm divides the positioning area into several sub-regions based on the discrete coefficient of the collected signal strength. Then, using the fitting method based on the signal intensity value of each sub-region, the algorithm derives the reference points of the logarithmic distance path loss model and path loss index. Finally, the algorithm locates target nodes using anchor nodes in different regions. Additionally, to enhance the positioning accuracy, weight values are assigned to the positioning result based on the discrete coefficient of the signal intensity in each sub-region. Experimental results demonstrate that the proposed WSN algorithm has high precision in forest environments.

Approximate dynamic programming for condition-based node deployment in a wireless sensor network

The flexibility of deployment strategies combined with the low cost of individual sensor nodes allow wireless sensor networks (WSNs) to be integrated into a variety of applications. Network operations degrade over time as sensors consume a finite power supply and begin to fail. In this work we address the selective maintenance of a WSN through a condition-based deployment policy (CBDP) in which sensors are deployed over a series of missions. The main contribution is a Markov decision process (MDP) model to maintain a reliable WSN with respect to region coverage. Due to the resulting high dimensional state and outcome space, we explore approximate dynamic programming (ADP) methodology in the search for high quality CBDPs. Our model is one of the first related to the selective maintenance of a large-scale WSN through the repeated deployment of new sensor nodes with a reliability objective, and one of the first ADP applications for the maintenance of a complex WSN. Additionally, our methodology incorporates a destruction spectrum reliability estimate which has received significant attention with respect to network reliability, but its value in a maintenance setting has not been widely explored. We conclude with a discussion on CBDPs in a range of test instances, and compare the performance to alternative deployment strategies.

Clustering Algorithms and Optimization Strategies in WSNs: A State-of-the-Art Review

Wireless Sensor Networks (WSNs) have emerged as a groundbreaking technology for collecting data on various physical phenomena, offering the potential to revolutionize infrastructure systems. The paper provides an exhaustive exploration of the existing literature on clustering algorithms within WSNs and the diverse optimization techniques proposed for cluster head selection. A comprehensive analysis of various routing protocols, mobility-based solutions, and energy conservation strategies is presented, shedding light on their respective strengths and limitations. The examination encompasses a wide spectrum of approaches, including hierarchical cluster-based routing, mobile sensor integration, and energy-efficient techniques inspired by industry standards like ZigBee. The paper further explores ecological monitoring applications, redundancy reduction mechanisms, and power- efficient hierarchical routing protocols, offering valuable insights into their contributions to the field. This review paper aims to consolidate and synthesize the wealth of knowledge in the domain of clustering algorithms and optimization techniques for WSNs. By assessing the strengths and weaknesses of these methodologies, it seeks to provide a comprehensive resource for researchers and practitioners in the field, ultimately contributing to the advancement of energy-efficient and reliable wireless sensor networks. Keywords— APTEEN, EARP, ECCP, GPS, HEED, LEACH, PEGASIS, TEEN, WSN.

Enhancing network lifespan in wireless sensor networks using deep learning based Graph Neural Network

Inadequate energy of sensors is one of the most significant challenges in the development of a reliable wireless sensor network (WSN) that can withstand the demands of growing WSN applications. Implementing a sleep-wake scheduling scheme while assigning data collection and sensing chores to a dominant group of awake sensors while all other nodes are in a sleep state seems to be a potential way for preserving the energy of these sensor nodes. When the starting energy of the nodes changes from one node to another, this issue becomes more difficult to solve. The notion of a dominant set-in graph has been used in a variety of situations. The search for the smallest dominant set in a big graph might be time-consuming. Specifically, we address two issues: first, identifying the smallest possible dominant set, and second, extending the network lifespan by saving the energy of the sensors. To overcome the first problem, we design and develop a deep learning-based Graph Neural Network (DL-GNN). The GNN training method and back-propagation approach were used to train a GNN consisting of three networks such as transition network, bias network, and output network, to determine the minimal dominant set in the created graph. As a second step, we proposed a hybrid fixed-variant search (HFVS) method that considers minimal dominant sets as input and improves overall network lifespan by swapping nodes of minimal dominating sets. We prepared simulated networks with various network configurations and modeled different WSNs as undirected graphs. To get better convergence, the different values of state vector dimensions of the input vectors are investigated. When the state vector dimension is 3 or 4, minimum dominant set is recognized with high accuracy. The paper also presents comparative analyses between the proposed HFVS algorithm and other existing algorithms for extending network lifespan and discusses the trade-offs that exist between them. Lifespan of wireless sensor network, which is based on the dominant set method, is greatly increased by the techniques we have proposed.

Multi-Agent Modeling and Jamming-Aware Routing Protocols for Movable-Jammer-Affected WSNs.

Wireless sensor networks (WSNs) are widely used in various fields, and the reliability and performance of WSNs are critical for their applications. However, WSNs are vulnerable to jamming attacks, and the impact of movable jammers on WSNs' reliability and performance remains largely unexplored. This study aims to investigate the impact of movable jammers on WSNs and propose a comprehensive approach for modeling jammer-affected WSNs, comprising four parts. Firstly, agent-based modeling of sensor nodes, base stations, and jammers has been proposed. Secondly, a jamming-aware routing protocol (JRP) has been proposed to enable sensor nodes to weigh depth and jamming values when selecting relay nodes, thereby bypassing areas affected by jamming. The third and fourth parts involve simulation processes and parameter design for simulations. The simulation results show that the mobility of the jammer significantly affects WSNs' reliability and performance, and JRP effectively bypasses jammed areas and maintains network connectivity. Furthermore, the number and deployment location of jammers has a significant impact on WSNs' reliability and performance. These findings provide insights into the design of reliable and efficient WSNs under jamming attacks.

Cryptographic Data Security for Reliable Wireless Sensor Network

Wireless Sensor Networks (WSNs) are widely utilized in a variety of applications. Attackers might interfere with equipment, and eavesdrop on conversations. Attackers can also modify the data which has been communicated or connect unauthorized devices to the network if such devices are deployed in the physical environment. To ensure WSN security, messages exchanged between communicating nodes must be encrypted, and for encryption and decryption, the network must store a key. Consequently, Key management is of significant importance in achieving security in WSN. Obtaining such a key arrangement in a resource-constrained environment is required for secure and energy-efficient data transmission in WSN. Current algorithms have certain security issues, such as vulnerability to plaintext attacks, brute force attacks, side-channel attacks, and computational complexity. Cryptography along with clustering has been found to be a practical and efficient technique to improve the secure and energy-efficient data transmission in WSNs. In this article we have used an asymmetric Elliptic Curve Cryptography (ECC) method for key generation whereas encryption and decryption of data, has been done by a hybrid of Advanced Encryption Standard (AES) and ECC cryptography A novel algorithm has been developed that incorporates both techniques (Advanced Encryption Standard (AES) and ECC cryptography) along with clustering through standard LEACH protocol for improving energy efficiency, data security, and network lifetime. The proposed algorithm has been able to overcome the issue of key exchange that plagues AES, simpler than ECC and more reliable than AES. More significantly, it is able to encounter a variety of security threats including side-channel attacks. The proposed algorithm is better and has been compared to current techniques with respect to time complexity, encryption time and decryption time to demonstrate its efficacy.

Modeling of Packet Error Rate Distribution Based on Received Signal Strength Indications in OMNeT++ for Wake-Up Receivers.

Wireless sensor network (WSN) with energy-saving capabilities have drawn considerable attention in recent years, as they are the key for long-term monitoring and embedded applications. To improve the power efficiency of wireless sensor nodes, a wake-up technology was introduced in the research community. Such a device reduces the system's energy consumption without affecting the latency. Thereby, the introduction of wake-up receiver (WuRx)-based technology has grown in several sectors. The use of WuRx in a real environment without consideration of physical environmental conditions, such as the reflection, refraction, and diffraction caused by different materials, that affect the reliability of the whole network. Indeed, the simulation of different protocols and scenarios under such circumstances is a success key for a reliable WSN. Simulating different scenarios is required to evaluate the proposed architecture before its deployment in a real-world environment. The contribution of this study emerges in the modeling of different link quality metrics, both hardware and software metrics that will be integrated into an objective modular network testbed in C++ (OMNeT++) discrete event simulator afterward are discussed, with the received signal strength indicator (RSSI) for the hardware metric case and the packet error rate (PER) for the software metric study case using WuRx based on a wake-up matcher and SPIRIT1 transceiver. The different behaviors of the two chips are modeled using machine learning (ML) regression to define parameters such as sensitivity and transition interval for the PER for both radio modules. The generated module was able to detect the variation in the PER distribution as a response in the real experiment output by implementing different analytical functions in the simulator.

Sectoring Method for Improving Various QoS Parameters of Wireless Sensor Networks to Improve Lifespan of the Network

The wireless sensor network is set of distributed nodes, which are randomly deployed in sensor field to capture various parameters and send it to receiver station for further analysis and prediction. There are two types of protocols essential for communication. One is MAC protocol and another is routing protocol. Routing protocols are used for finding shortest path between sources to destination. MAC protocols are used for reliable data delivery from source to destination. The design of a reliable wireless sensor network (WSN) must handle the failure of single or many network components, still, because of the deployment of mechanisms to tolerate faults at various levels. the most objective of this paper is to review different existing algorithms proposed by different researchers and merge their work for further study. This paper studies different prototypes and proposed algorithms, and also the objectives of the papers. Also, the paper elaborates on the proposed algorithm within the particular paper together with their objectives. Proposed algorithm is very useful for to reduce heavy congestion over the networks and achieve various parameters of sensor networks.

Adaptive coding clustered routing protocol for energy efficient and reliable WSN

In Wireless Sensor Networks (WSNs), the sensor nodes are expected to remain autonomous for a long time and the communication must be successful. So, energy efficiency and communication reliability are the main challenges for WSN. Routing protocols and, in particular, clustering is the key to energy constraints in WSNs. In a loss milieu, data shared between nodes is susceptible to corruption by errors caused by signal fading, random noise, and some other forces. For this reason, channel coding is necessary to assure efficient and reliable transmission. Therefore, energy efficiency and reliability of communications are the most crucial factors in the design of an efficient cluster-based routing protocol. In this context, to raise the reliability of the communication link and minimize the necessary transmission energy, a new adaptive coding routing protocol is proposed, which implements RS and LDPC codes to a routing protocol. Simulation results show that our proposed protocol improves energy consumption, network lifetime, stability, and throughput compared to LEACH and BRE-LEACH. In addition, it reaches a good BER performance and coding gain by using the LDPC code.

Development of Energy Efficient and Optimized Coverage Area Network Configuration to Achieve Reliable WSN Network Using Meta-Heuristic Approaches

Energy optimization and coverage area optimization of wireless sensor networks (WSN) are two major challenges to accomplish reliability optimization in the field of WSN. Reliability optimization in the field of WSN is directly connected to the performance and efficiency and consistency of the network. In this paper, the authors describe how these challenges can be resolved by designing an efficient WSN with the help of meta-heuristic algorithms. They have configured an optimized route/path using ant colony optimization (ACO) algorithm and deployed static WSN nodes. After configuring an efficient network, if we can maximize the coverage area, then we can ensure that the network is a reliable network. For coverage area optimization, they used a hybrid differential evolution-quantum behaved particle swarm optimization (DE-QPSO) algorithm. The result has been compared with existing literature, and the authors found good results applying those meta-heuristic and hybrid algorithms.

Genetic algorithm optimized node deployment in IEEE 802.15.4 potato and wheat crop monitoring infrastructure

This proposal investigates the effect of vegetation height and density on received signal strength between two sensor nodes communicating under IEEE 802.15.4 wireless standard. With the aim of investigating the path loss coefficient of 2.4 GHz radio signal in an IEEE 802.15.4 precision agriculture monitoring infrastructure, measurement campaigns were carried out in different growing stages of potato and wheat crops. Experimental observations indicate that initial node deployment in the wheat crop experiences network dis-connectivity due to increased signal attenuation, which is due to the growth of wheat vegetation height and density in the grain-filling and physical-maturity periods. An empirical measurement-based path loss model is formulated to identify the received signal strength in different crop growth stages. Further, a NSGA-II multi-objective evolutionary computation is performed to generate initial node deployment and is optimized over increased coverage, reduced over-coverage, and received signal strength. The results show the development of a reliable wireless sensor network infrastructure for wheat crop monitoring.

Time-Based Node Deployment Policies for Reliable Wireless Sensor Networks

Wireless sensor networks (WSNs) are commonly used to monitor a remote environment over an extended period of time. One important design consideration is the WSN's reliability of area coverage, as sensors fail over time and functionality of the network degrades. When the WSN no longer sufficiently covers the region, maintenance actions may consider repairing failed nodes or deploying new sensors to re-establish network capability. Toward identifying an optimal maintenance policy, specifically the deployment of new sensors, in this article, we present an optimization model formulated using the network destruction spectrum (D-spectrum), which seeks to determine a time-based deployment policy balancing cost and reliability. While the benefits of using the D-spectrum in reliability are widely researched, the application of the D-spectrum to enable the modeling and solving of an optimization problem is new. With the complexity already present in estimating reliability, the significance of this optimization model is that it decouples the complexity of estimating the D-spectrum from the estimation of network reliability in the presence of a given deployment policy. This key feature allows us to quickly evaluate a wide range of time-based deployment policies. Additionally, we present an efficient destruction algorithm that performs a vital subroutine in estimating the D-spectrum, allowing for a large number of replications to be performed in the Monte Carlo simulation, thereby reducing the variance of the resulting reliability estimate. Finally, the optimization model is illustrated through a numerical example.

DAG-Coder: Directed Acyclic Graph-Based Network Coding for Reliable Wireless Sensor Networks

Wireless sensor devices are usually powered with limited non-rechargeable batteries. This energy can easily be depleted when no wise consumption procedures are used, leaving the sensor non-functional. As most of the energy is consumed during the transmission of data, developing efficient data manipulation and transmission approaches is crucial and still an open problem that attracts the attention of many research groups. In this article a directed acyclic graph (DAG) based dissemination approach, where clustering and network coding techniques are applied, is proposed. As a main goal, this work aims at improving the network reliability (ensure recovery of lost packets), while minimizing energy consumption and balancing load at gateways. The proposed approach is compared to state-of-art approaches in terms of network reliability and energy saving trade-off. Experimental results demonstrate the strong performance of the proposed work.

Self Configuring Wireless Sensor Network for Precision Irrigation

Precision Irrigation is a farm management strategy used to increase the water efficiency of a farm in which the right amount of water is fed to the soil at right time by sensing the real time soil conditions in the field. Wireless Sensor Network (WSN) Technology is widely used in farms to measure soil conditions at various locations of the farm and use the data for making decisions in the areas to be irrigated with the right amount of water. This project presents the design and development of a self organizing and fault tolerant ad-hoc multi-hop WSN for precision irrigation using low cost commercially available electronic components. This includes the design and development of hardware units for Sensor Nodes to be deployed in the field for the measurement of soil humidity and a centralized Base Station to collect the information from the nodes and make decisions on irrigating. A reliable multi-hop WSN system with ad-hoc routing algorithm for prolonged lifetime and fault tolerance has been developed and demonstrated using field trials and lab level simulations. The project also developed a user interface to monitor and archive the data acquired through the network.

Reliable wireless multimedia sensor network design: comparison of hybrid metaheuristics and a matheuristic

Network reliability has vital importance for designing wireless multimedia sensor networks (WMSNs). The definition of network reliability for WMSNs differentiates from the traditional communication network types which simultaneously involves node deployment, connectivity and coverage issues. Therefore, in this study, a new information gathering network reliability definition is made for WMSNs. The information gathering network reliability is maximized under a given total budget constraint by including node and terrain characteristics. The model is developed to get surveillance from an enemy zone. Since the reliable WMSN design considering node deployment, connectivity and coverage has NP-hard complexity, new hybrid methods are proposed with hybridization of exact methods with nature-inspired metaheuristics. Five algorithms are generated. Firstly, problem-specific simulated annealing (SA) and genetic algorithm (GA) are developed, then branch and bound (B&B) is embedded into the SA and GA named as hybrid SA (HSA) and hybrid GA (HGA). The B&B method optimizes the orientations of the sensor nodes. Additionally, an HGA-based matheuristic (HGABM) is proposed. In HGABM, a mixed integer linear programming (MILP) network flow-based model is added into the initial population generation procedure of the HGA. The MILP model finds the exact deployment points of the relay nodes. In experimental study, it is noticed that the main time-consuming parts of the algorithms are network reliability calculations. Thence, a parallel Monte Carlo (MC) simulation is developed and the MC runs are made in multiple general purpose graphics processing units (GPGPUs). Full-factorial experimental design and Taguchi design approaches are preferred to tune the parameters, to generate the problem sets and to make the experiments. The experimental study is performed on synthetically generated terrains with different terrain and device-based scenarios. Statistical methods are used to compare the performances of the algorithms. In conclusion, for small-sized sets HGABM and for moderate- and large-sized sets, HGA outperforms the other algorithms. The algorithms are coded in MATLAB and the MILP model is solved with CPLEX.

A System-Level Methodology for the Design of Reliable Low-Power Wireless Sensor Networks.

Innovative Internet of Things (IoT) applications with strict performance and energy consumption requirements and where the agile collection of data is paramount are arising. Wireless sensor networks (WSNs) represent a promising solution as they can be easily deployed to sense, process, and forward data. The large number of Sensor Nodes (SNs) composing a WSN are expected to be autonomous, with a node’s lifetime dictated by the battery’s size. As the form factor of the SN is critical in various use cases, minimizing energy consumption while ensuring availability becomes a priority. Moreover, energy harvesting techniques are increasingly considered as a viable solution for building an entirely green SN and prolonging its lifetime. In the process of building a SN and in the absence of a clear and well-rounded methodology, the designer can easily make unfounded and suboptimal decisions about the right hardware components, their configuration, and reliable data communication techniques, such as automatic repeat request (ARQ) and forward error correction (FEC). In this paper, a methodology to design, configure, and deploy a reliable ultra-low power WSNs is proposed. A comprehensive energy model and a realistic path-loss (PL) model of the sensor node are also established. Through estimations and field measurements it is proven that, following the proposed methodology, the designer can thoroughly explore the design space and the make most favorable decisions when choosing commercial off-the-shelf (COTS) components, configuring the node, and deploying a reliable and energy-efficient WSN.

An Enhanced Vitality Efficient and Reliable Wireless Sensor Networks with CRT-Based Packet Breaking Scheme

Wireless sensor networks (WSNs) consist of a large number of wireless sensor nodes dispersed in an area of interest with one or more base stations mainly used in monitoring our environment and also for physical conditions. It has been established that energy is the most constraining factor on the functionality of such networks because they are powered with limited energy and replacement of power resources might be unfeasible. Duty Cycling and In-Network Aggregation could be used to reduce energy consumption but energy saving is obtained at the expense of an increased node complexity and network latency. However, in order to reduce energy consumption and increase reliability, nodes only need to send small packet to the sink. A secured and energy efficient wireless sensor network using Chinese Remainder Theorem (CRT) based packet splitting algorithm is therefore proposed. This technique involves splitting the messages sent by the source node of a wireless sensor network so that the maximum number of bits per packet that a node has to forward is reduced which decreases the energy consumption of the network. However, it also increases the message security because the remainders of sensed data are sent instead of data itself, the received packet is encrypted and for decrypt the message, need to have the moduli set which serves as the secret key. The results obtained shows the proposed algorithm outperforms traditional approaches in terms of energy saving, reliability, simplicity and fair distribution of energy consumption among all nodes in the network as well as reduction in end-to-end delay.

Dominating Set Algorithms for Wireless Sensor Networks Survivability

Limited energy of the sensors is one of the key issues towards realizing a reliable wireless sensor network (WSN), which can survive under the emerging WSN applications. A promising method for conserving the energy of these sensors can be implemented by applying a sleep-wake scheduling while distributing the data gathering and sensing tasks to a dominating set of awake sensors while the other nodes are in a sleep mode. Producing the maximum possible number of such disjoint dominating sets, called the domatic partition problem in unit disk graphs, can further prolong the network lifetime. This problem becomes challenging when the initial energy of the nodes varies from one to another. In this paper, we introduce multiple local search algorithms that can improve the total lifetime of WSNs consisting of nodes with varying initial energy. We discuss the performance of the existing dominating set algorithm and introduce three more algorithms which can be applied on multiple disjoint dominating sets with nodes having varying initial energy. We discuss the efficiency of each of the algorithms through extensive simulations.

Reliable and energy efficient wireless sensor network design via conditional multi-copying for multiple central nodes

Design of reliable wireless sensor networks considering energy efficiency is of utmost importance given their specific application domains and technical properties. As a contribution to the vast literature on resilient and fault tolerant network design, this paper offers a novel energy efficient conditional multi-copy and multi-path routing strategy. The motivation is to use limited energy of sensors as efficiently as possible and to improve network reliability and security via restricted redundant data generation. Namely, rather than all only the data passing through some central nodes are duplicated as a precaution against their malfunctioning. A limited number of nodes with higher data transmission allowance are determined as central at the design stage considering lifetime maximization objective. Consequently, 0–1 mixed integer programming models of two variants of the proposed strategy are presented in order to determine optimal routing. Moreover, several valid inequalities so as to improve solution times with commercial solvers and an efficient heuristic method for finding good solutions for large instances in reasonable times are proposed. Extensive test results show that simple restricted multi-copy strategies where every sensor duplicates its data are improved since the proposed strategies provide comparable levels of network reliability and yet extend network lifetime significantly.

An Ant Colony Optimization Approach for the Deployment of Reliable Wireless Sensor Networks

A reliable wireless sensor network (WSN) is defined as a network that functions satisfactorily, in terms of both its coverage and connectivity to the sink(s), throughout its intended mission time. Deploying reliable WSNs is especially important for critical Internet of Things (IoT) applications, such as industrial, structural health-monitoring, and military applications. In such applications, failure of the WSN to carry out its required tasks can have serious effects, and hence, cannot be tolerated. However, the deployment of reliable WSNs is a challenging problem. This is primarily attributed to the fact that sensor nodes are subject to random failures due to different factors, such as hardware failures, battery depletion, harsh environmental conditions, and so on. In this paper, the problem of deploying a WSN with a specified minimum level of reliability at a minimum deployment cost is addressed. This problem is coined the minimum cost reliability constrained sensor node deployment problem (MCRC-SDP). The MCRC-SDP is proved to be an NP-Complete. An ant colony optimization algorithm coupled with a local search heuristic is proposed as a solution. Extensive experimental results demonstrate the effectiveness of the proposed approach in finding high-quality solutions to the problem.