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"wireless sensor network"
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Localization in Wireless Sensor Networks: A Survey on Algorithms, Measurement Techniques, Applications and Challenges
Localization is an important aspect in the field of wireless sensor networks (WSNs) that has developed significant research interest among academia and research community. Wireless sensor network is formed by a large number of tiny, low energy, limited processing capability and low-cost sensors that communicate with each other in ad-hoc fashion. The task of determining physical coordinates of sensor nodes in WSNs is known as localization or positioning and is a key factor in today’s communication systems to estimate the place of origin of events. As the requirement of the positioning accuracy for different applications varies, different localization methods are used in different applications and there are several challenges in some special scenarios such as forest fire detection. In this paper, we survey different measurement techniques and strategies for range based and range free localization with an emphasis on the latter. Further, we discuss different localization-based applications, where the estimation of the location information is crucial. Finally, a comprehensive discussion of the challenges such as accuracy, cost, complexity, and scalability are given.
Journal Article
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.
Journal Article
Research of localization algorithm for wireless sensor network based on DV-Hop
Wireless sensor network (WSN) possesses very broad application prospect in many fields, where the node location technology is one of the key technologies of WSN. Distance vector hop (DV-Hop) localization algorithm is a widely used algorithm in this technology, and it uses routing exchange protocol to make unknown nodes obtain beacon node information which will be used for coordinate calculation, therefore there exists certain error for the algorithm itself. Aiming at the disadvantage of large error existing in the traditional wireless sensor network location algorithm based on DV-Hop, an improved DV-Hop algorithm based on hop thinning and distance correction is proposed. The minimum hop is corrected by introducing received signal strength indication (RSSI) ranging technology, and the average hop distance is corrected by weighted average value of hop distance error and estimated distance error. Subsequently, the overall improvement on the location performance of the Hop-DV location algorithm is realized, and the location error is reduced. Under the Matlab simulation environment, the simulation experiment on the improved algorithm is carried out. The experimental results show that the improved algorithm reduces the location error and has higher location accuracy.
Journal Article
Routing Protocols for UAV-Aided Wireless Sensor Networks
Recently, unmanned aerial vehicles (UAVs) attracted significant popularity in both military and civilian domains for various applications and services. Moreover, UAV-aided wireless sensor networks (UAWSNs) became one of the interesting hot research topics. This is mainly because UAWSNs can significantly increase the network coverage and energy utilization compared to traditional wireless sensor networks (WSNs). However, the high mobility, dynamic path, and variable altitude of UAVs can cause not only unforeseen changes in the network topology but also connectivity and coverage problems, which can affect the routing performance of the network. Therefore, the design of a routing protocol for UAWSNs is a critical task. In this paper, the routing protocols for UAWSNs are extensively investigated and discussed. Firstly, we classify the existing routing protocols based on different network criteria. They are extensively reviewed and compared with each other in terms of advantages and limitation, routing metrics and policies, characteristics, difference performance factors, and different performance optimization factors. Furthermore, open research issues and challenges are summarized and discussed.
Journal Article
ISFO-CS: An Improved Sailfish Optimization Algorithm for Controller Selection in SDWSN
Software-defined wireless sensor networks (SDWSNs) have recently been added to networking, increasing scalability and performance. Choosing SDN controllers is a critical issue for network administrators in SDNs. The control plane in SDN is a separate procedure that operates on the control layer. In terms of applications and services, the controller provides a comprehensive view of the entire network. The three key factors examined when selecting a controller are open source, campus network, and productivity. An appropriate device for the prompt processing of all switch requests is required for SDN to function properly and the network to behave properly. To determine the optimum controller for the given parameters, decision logic that allows controller comparison must be developed. As a result, an improved Sailfish Optimization based controller selection (ISFO-CS) method is proposed in this study to ideally take the best controller node (CN) from a group of sensor nodes. The ISFO selects the best CN by considering a multi-objective fitness function incorporating distance, residual energy, node coverage, and sensor node communication cost. After selecting CN, the Fuzzy C-means (FCM) Clustering algorithm executes the subsequent data transmission process. The Matlab program is used to execute the simulation, and the performance of the proposed ISFO-CS methodology is assessed using several performance criteria. The proposed ISFO-CS model accomplishes a 95% packet delivery ratio for 500 rounds, consumes less energy of 0.13 mJ, and takes 1.8 s for 500 rounds of node to controller latency.
Journal Article
A modified cluster-head selection algorithm in wireless sensor networks based on LEACH
In order to overcome drawbacks of unreasonable cluster-head selection and excessive energy consumption in wireless sensor networks (WSNs), a modified cluster-head selection algorithm based on LEACH (LEACH-M) was proposed. Based on distributed address assignment mechanism (DAAM) of ZigBee, both residual energy and network address of nodes were taken into account to optimize cluster-head threshold equation. Furthermore, by leveraging a cluster-head competitive mechanism, LEACH-M successfully balanced the network energy burden and dramatically improved energy efficiency. The simulation results in NS-2.35 show that the proposed algorithm can prolong the network lifetime, minimize the energy consumption, and increase the amount of data received at base station whether region is in a 100 × 100m2or in a 300 × 300m2.
Journal Article
Localization in wireless sensor networks and wireless multimedia sensor networks using clustering techniques
Localization in wireless sensor networks (WSN) is gaining a lot of attention from the researchers due to its usefulness in many real-time applications to identify the source of events. Wireless sensor networks are also utilized to transmit multimedia data such as audio, video and images along with scalar data. This type of WSN is termed as Wireless Multimedia Sensor Network (WMSN). Many applications exist, such as battlefields, environmental monitoring, ecosystem monitoring, and forest fire detection, among others, where the source of an event’s occurrence is critical. As a result, using simulations or simulating real-time scenarios, researchers have developed various techniques for locating sensor nodes in wireless sensor networks. This paper presents the clustering-based localization strategies for WSN and WMSN in detail. In a wireless sensor network and wireless multimedia sensor networks, clustering is utilized to offer distributed computing and parallel processing by grouping sensor nodes into small subgroups that operate independently. To improve the performance of the traditional localization procedure, clustering techniques might be greatly useful. Clustering divides the network into partitions which can independently function thus reducing the communication cost. Clustering also increases the throughput of the network by providing distributed computing. Furthermore, future concerns and issues are highlighted in order to determine the future study direction for new wireless sensor network researchers.
Journal Article
Energy Consumption Reduction in Wireless Sensor Network-Based Water Pipeline Monitoring Systems via Energy Conservation Techniques
In wireless sensor network-based water pipeline monitoring (WWPM) systems, a vital requirement emerges: the achievement of low energy consumption. This primary goal arises from the fundamental necessity to ensure the sustained operability of sensor nodes over extended durations, all without the need for frequent battery replacement. Given that sensor nodes in such applications are typically battery-powered and often physically inaccessible, maximizing energy efficiency by minimizing unnecessary energy consumption is of vital importance. This paper presents an experimental study that investigates the impact of a hybrid technique, incorporating distributed computing, hierarchical sensing, and duty cycling, on the energy consumption of a sensor node in prolonging the lifespan of a WWPM system. A custom sensor node is designed using the ESP32 MCU and nRF24L01+ transceiver. Hierarchical sensing is implemented through the use of LSM9DS1 and ADXL344 accelerometers, distributed computing through the implementation of a distributed Kalman filter, and duty cycling through the implementation of interrupt-enabled sleep/wakeup functionality. The experimental results reveal that combining distributed computing, hierarchical sensing and duty cycling reduces energy consumption by a factor of eight compared to the lone implementation of distributed computing.
Journal Article
Heuristic Algorithms and Linear Programming for Energy Optimization in Three‐Dimensional Wireless Sensor Networks
Optimizing the energy consumption of three‐dimensional wireless sensor networks (3D‐WSNs) is significantly more difficult than optimizing that of two‐dimensional WSNs. This is primarily because of the additional spatial dimension, which introduces further computational and operational complexity to the network. Recently, a new method based on mixed‐integer linear programming (MILP) was introduced to address the energy efficiency problem of 3D‐WSNs. However, this method relies on unrealistic assumptions, which limit its practical applicability. Specifically, it is assumed that networks consist of randomly deployed unlimited energy sink nodes. The random placement of sink nodes degrades the network performance, and the assumption of infinite energy for the sink nodes makes the model impractical for real‐world scenarios. To address these shortcomings, this paper proposes a novel method that combines the differential evolution (DE) algorithm with MILP, referred to as hybrid DE‐MILP, to optimize energy usage and extend the lifetime of 3D‐WSNs. Unlike the MILP approach, the proposed method eliminates the need for sink nodes. Instead, it identifies cluster heads (CHs) from among finite‐energy sensor nodes using a heuristic strategy. Once the CHs are selected, linear programming is employed to determine the most energy‐efficient communication path among the nodes. Our approach is more practical and better suited for real‐world deployment because it relies solely on homogeneous sensor nodes with limited energy. The proposed method was evaluated and compared with MILP and multihop low‐energy adaptive clustering hierarchy (MH‐LEACH) algorithms. Simulation results demonstrated that the proposed approach significantly outperforms both the MILP and MH‐LEACH methods. Specifically, our method reduces the energy consumption by at least 13% and 48% compared with the MILP and MH‐LEACH methods, respectively. This reduction in network energy consumption improved the network lifetime by at least 28% and 70%, respectively. The results of this study demonstrate that the hybrid DE‐MILP approach is a robust and scalable framework for practical 3D‐WSN deployment.
Journal Article