Localization in WSN Research Papers (original) (raw)

2025, The World Internet and Electronic Cities Conference

This paper addresses the problem of testing an automated fingerprint comparison system. In this research, a web-based test bed is developed to assist the experiments in Fingerprint Image Comparison (FIC). The FIC function, which supports the comparison between submitted fingerprints and candidate fingerprint, is one of the specified functions of the US Federal Bureau of Investigation (FBI) Integrated Automated Fingerprint Identification System (IAFIS). The FIC test bed provides an integrated environment to simplify the testing ...

2025, IEEE Sensors Journal

This paper introduces two main contributions to the wireless sensor network (WSN) society. The first one consists of modeling the relationship between the distances separating sensors and the received signal strength indicators (RSSIs) exchanged by these sensors in an indoor WSN. In this context, two models are determined using a radio-fingerprints database and kernel-based learning methods. The first one is a non-parametric regression model, while the second one is a semi-parametric regression model that combines the well-known log-distance theoretical propagation model with a non-linear fluctuation term. As for the second contribution, it consists of tracking a moving target in the network using the estimated RSSI/distance models. The target's position is estimated by combining acceleration information and the estimated distances separating the target from sensors having known positions, using either the Kalman filter or the particle filter. A fully comprehensive study of the choice of parameters of the proposed distance models and their performances is provided, as well as a study of the performance of the two proposed tracking methods. Comparisons to recently proposed methods are also provided.

2025, IEEE Sensors Journal

2025, 2010 International Conference on Indoor Positioning and Indoor Navigation

For locating a set of stationary devices, algorithms such as MDS-MAP have been favoured by the sensor network community. This is generally because of their low computational complexity. Whilst comparisons for complexity and performance have been done for other algorithms, non-linear regression (NLR) has been neglected. The authors find that it is not much more expensive than MDS-MAP, yet can yield significantly better accuracy for sensor network localisation.

2025

Localization is a prominent part of the Wireless Sensor Networks (WSN), as without the location information, messages are bound to be invalid on network. Various techniques have been introduced to localize the unknown nodes in the network. The efficiency of localization algorithms depend on the accuracy of localizing the nodes, precisely. The anchor nodes are always limited because of hardware restrictions like energy consumptions, cost etc. The primary objective of this task is to achieve the least localization error. In order to achieve this objective, centroid algorithm is refined in the grid environment. The grid environment provides a regular deployment of the anchor nodes. The derived technique uses the concept of weight and distance to improve the accuracy and the simulation results manifest the superior performance. Keywords— Localization; Anchor nodes; Centroid; Unknown nodes; Grid deployment

2025, Journal of Computer Science and Control Systems

The sensor networks are becoming important in many areas; these networks are facing several problems, the most important problem of the exploitation of the energy properly and how to extend the lifetime of the network. In sensor networks, LEACH protocol is used widely to reduce energy consumption. In this research, we present improvements to the original LEACH protocol, in order to increase its efficiency in processing to reduce energy consumption and therefore an increase in the network lifetime where, network area (100×100 m 2) was divided into two halves and the following improvements were added: 1. The idea of LEACH-C protocol was used in the first round only. 2. 2 BSs were added to the network (each BS receives data from half the area of the network) instead of one BS then; the data of 2 BSs were sent to the main server and that was helped in saving energy. 3. The choice CHs was prevented in the region far from the BSs (where 5 meters per BS had been identified). Through these improvements, a good results were gotten in the simulation, which demonstrate that the improved LEACH protocol was better and more efficient than the original LEACH protocol of several things: the expansion in the network lifetime, survival of more of nodes alive during the rounds (which means gathering more of information), as well as remaining of nodes alive after the implementation.

2025, International Journal of Advances in Engineering Sciences

‫ـ‬ ‫ــ‬ LEACH protocol is one of the widely used protocols in wireless sensor networks (WSN), in which a reduction of energy consumption is the main task. This protocol was encountered several problems such as, the node did not choose the best cluster head (Even if the cluster head closer to that node), which may be far from the Base Station, which was leaded to consume more energy, and hence network lifetime will be short. In the present work, an improvement was added to the original LEACH protocol by making the node associated with the appropriate CH that may not be the closest to it. This improvement was accomplished by calculating the distance between the node and the BS (distance1) and that between the CH and BS (distance2), if (distance2) < (0.5*distance1), it was meant that the current CH is the best. The improved LEACH protocol was simulated using Matlab software. The simulation results were shown that the improved protocol was given better performance than the original one of the following aspects: 1-Increasing the number of rounds. 2-Delayed the first node dies. 3-Deceleration in the total nodes death. 4-Balance in the energies of the nodes. 5-Extended the overall network lifetime.

2025

As Wireless Sensor Network (WSN) has become a key technology for different types of smart environment, nodes localization in WSN has arisen as a very challenging problem in the research community. Most of the applications for WSNs necessitate a priory known nodes positions. In this paper, we propose an algorithm for three dimensional (3D) nodes localization in surface WSN based on multidimensional scaling (MDS) technique. Using extensive simulations, we investigated in details our approach regarding different network topologies, various network parameters and performance issues. The results from simulations show that our algorithm produces small localization error and outperforms MDS-MAP in terms of accuracy.

2025

Wireless communication itself consumes the most amount of energy in a given WSN, so the most logical way to reduce the energy consumption is to reduce the number of radio transmissions. To address this issue, there have been developed data reduction strategies which reduce the amount of sent data by predicting the measured values both at the source and the sink, requiring transmission only if a certain reading differ by a given margin from the predicted values. While these strategies often provide great reduction in power consumption, they need a-priori knowledge of the explored domain in order to correctly model the expected values. Using a widely known mathematical apparatus called the Least Mean Square Algorithm (LMS), it is possible to get great energy savings while eliminating the need of former knowledge or any kind of modeling. In this paper with we use the Least Mean Square Algorithm with variable step size (LMS-VSS) parameter. By applying this algorithm on real-world data s...

2025, Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology - CSTST '08

Nodes localization in Wireless Sensor Networks (WSN) has arisen as a very challenging problem in the research community. Most of the applications for WSN are not useful without a priori known nodes positions. One solution to the problem is by adding GPS receivers to each node. Since this is an expensive approach and inapplicable for indoor environments, we need to find an alternative intelligent mechanism for determining nodes location. In this paper, we propose our cluster-based approach of multidimensional scaling (MDS) technique. Our initial experiments show that our algorithm outperforms MDS-MAP[8], particularly for irregular topologies in terms of accuracy.

2025, ICT Innovations 2009

With the recent development of technology, wireless sensor networks are becoming an important part of many applications such as health and medical applications, military applications, agriculture monitoring, home and office applications, environmental monitoring, etc. Knowing the location of a sensor is important, but GPS receivers and sophisticated sensors are too expensive and require processing power. Therefore, the localization wireless sensor network problem is a growing field of interest. The aim of this paper is to give a comparison of wireless sensor network localization methods, and therefore, multidimensional scaling and semidefinite programming are chosen for this research. Multidimensional scaling is a simple mathematical technique widely-discussed that solves the wireless sensor networks localization problem. In contrast, semidefinite programming is a relatively new field of optimization with a growing use, although being more complex. In this paper, using extensive simulations, a detailed overview of these two approaches is given, regarding different network topologies, various network parameters and performance issues. The performances of both techniques are highly satisfactory and estimation errors are minimal.

2025, Communications of the ACM

The iBracelet and the Wireless Identification and Sensing Platform promise the ability to infer human activity directly from sensor readings.

2025

Localization is one of the significant techniques in wireless sensor networks. The localization approaches are different in several applications. Localization offers geographical information for managing the topology. In this paper, we propose optimized cooperative localization technique based on trilateration, multilateration and linear intersection. The approach reduces the error rates, communication cost and energy consumption for maintaining the high accuracy. Furthermore, the approach is implemented for controlling air craft system to avoid the landing and takeoff delays. To demonstrate the strength of the approach, we used network simulator ns-2 to validate the estimation errors, computational latency, energy consumption and error tolerance. Based on the simulation results, we conclude that the presented approach outperforms other existing cooperative scheduling approaches in terms of accuracy, mobility, consumed power.

2025, International Journal of Computer Information Systems and Industrial Management Applications.

2025, Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics

The recent advancements of Radio Frequency IDentification (RFID)-based localization approach has necessitates the development of effective solutions for mobile robot navigation systems in an indoor and/or outdoor environment. Among the most common problems pertaining to the modern RFID-based robot navigation systems are that multiple reference RF stations or excessive number of sensors are utilized for the location sensing with RFID, however, particularly in indoor environments, spatial layout or cost problems limit the applicability of those approaches. The contribution of the current manuscript is to devise a simple computationally efficient relative positioning system for indoor environments through a modified RFID tag architecture. The validity of the proposed RFID-based RPS is demonstrated using the real data collected in a typical indoor environment. NOMENCLATURE N Total number of RFID tags p Estimated robot position p True robot position p i Position of tag i ê Robot position error ∆RSS Received signal strength difference RSS i Average RSS value of tag i RSS ji j th RSS value of tag i

2025, Indian Journal of Science and Technology

This paper presents a new approach for self localization of wireless sensors. Various algorithms have been proposed for localization of wireless sensor networks and are based on computational measurements. The suggested approaches estimate the location of sensors implemented with concepts of functionalities and future scopes. The proposed algorithm relies on a range measurement technique between a pair of nodes and their arrangement to cover maximum area surrounding the main node. Hence, a confident position of sensor is established. The evident advantage of the algorithm is that it requires less number of sensor nodes and saves the constructional cost of a wireless sensor network.

2025, International Journal of Computer Information Systems and Industrial Management Applications.

As research in Node localization in WSN becomes ubiquitous, there is a dire need to interpret and map the increasing scientific knowledge and evolutionary trends so that a firm foundation can be laid for identifying knowledge gaps and advancing the domain. There is a critical need to interpret and map the expanding body of scientific knowledge and evolutionary trends as Node localization research in WSN spreads widely to establish a solid foundation for identifying knowledge gaps and developing the domain. Hence, this study aims to undertake a bibliometric analysis of node localization approaches. The Scopus central assemblage database was searched for titles that included "node localization", "wireless sensor network," and "WSN". A total of 1618 documents were published within the nineteen-study period (2003-2022). Microsoft Excel 365, R Bibliometric and Biblioshiny packages were implored for statistical analysis of approved published research articles. This study highlights the trends and current state of node localization research in WSN. It can aid researchers in gaining a thorough understanding of the most recent node localization techniques used in WSN.

2025, arXiv (Cornell University)

Traditional algorithms for robots who need to integrate into a wireless network often focus on one specific task. In this work we want to develop simple, adaptive and reusable algorithms for real world applications for this scenario. Starting with the most basic task for mobile wireless network nodes, finding the position of another node, we introduce an algorithm able to solve this task. We then show how this algorithm can readily be employed to solve a large number of other related tasks like finding the optimal position to bridge two static network nodes. For this we first introduce a meta-algorithm inspired by autonomous robot learning strategies and the concept of internal models which yields a class of source seeking algorithms for mobile nodes. The effectiveness of this algorithm is demonstrated in real world experiments using a physical mobile robot and standard 802.11 wireless LAN in an office environment. We also discuss the differences to conventional algorithms and give the robotics perspective on this class of algorithms. Then we proceed to show how more complex tasks, which might be encountered by mobile nodes, can be encoded in the same framework and how the introduced algorithm can solve them. These tasks can be direct (cross layer) optimization tasks or can also encode more complex tasks like bridging two network nodes. We choose the bridging scenario as an example, implemented on a real physical robot, and show how the robot can solve it in a real world experiment.

2024, International Journal of Innovative Research in Computer Science and Technology (IJIRCST)

Wireless Sensor Networks (WSNs), accurate and energy-efficient localization of sensor nodes remains a challenging task despite significant advancements. Current geolocation algorithms often struggle with scalability, adaptability, and energy efficiency, particularly in large-scale, dynamic environments where node failures or random shifts occur. This paper proposes a novel Secure Node Localization (SABWP-NL) approach, combining Self-Adaptive Binary Waterwheel Plant Optimization (SABWP) and Bayesian optimization to enhance localization accuracy, scalability, energy efficiency, and robustness. The method evaluates node trust using Dempster-Shafer Evidence Theoryto secure localization against rogue nodes and optimizes the localization process through trilateral and multilateration systems. The SABWP-NL approach demonstrates superior performance in terms of localized nodes and localization error compared to existing techniques like BWP, ROA, and AO. Results show that SABWP-NL achieves the highest number of localized nodes and the lowest localization error, making it a promising solution for efficient and secure node localization in WSNs.

2024

Multi-hop data delivery through Vehicular Adhoc Networks is challenging since it must efficiently handle rapid topology changes and a fragmented network. This paper proposes a new intersection-based geographical routing protocol called GyTAR (improved Greedy Traffic Aware Routing protocol) and capable to find robust routes within city environments. GyTAR consists of two modules: (i) dynamic selection of the junctions through which a packet must pass to reach its destination, and (ii) an improved greedy strategy used to forward packets between two junctions. GyTAR assumes the existence of an accurate traffic-information system that it requires to select paths with high connectivity. To address this issue, we also propose a completely decentralized mechanism for the estimation of traffic density in city-roads called IFTIS for Infrastructure-Free Traffic Information System. The proposed routing protocol shows significant performance improvement in a comparative simulation study with other routing approaches.

2024, HAL (Le Centre pour la Communication Scientifique Directe)

We present a novel FastSLAM approach for a robotic system inspecting structures made of large metal plates. By taking advantage of the reflections of ultrasonic guided waves on the plate boundaries, it is possible to recover, with enough precision, both the plate shape and the robot trajectory. Contrary to our previous work, this approach takes into account the dispersive nature of guided waves in metal plates. This is leveraged to construct beamforming maps from which we solve the mapping problem through plate edges estimation for every particle, in a FastSLAM fashion. It will be demonstrated, with real acoustic measurements obtained on different metal plates, that such a framework achieves better results in terms of convergence and accuracy, while the complexity of the algorithm is sensibly reduced.

2024, 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing

In recent years, indoor localization has become a hot research topic with some sophisticated solutions reaching accuracy on the order of ten centimeters. While certain classes of applications can justify the corresponding costs that come with these solutions, a wealth of applications have requirements that can be met at much lower cost by accepting lower accuracy. This paper explores one specific application for monitoring patients in a nursing home, showing that sufficient accuracy can be achieved with a carefully designed deployment of low-cost wireless sensor network nodes in combination with a simple RSSI-based localization technique. Notably our solution uses a single radio sample per period, a number that is much lower than similar approaches. This greatly eases the power burden of the nodes, resulting in a significant lifetime increase. This paper evaluates a concrete deployment from summer 2012 composed of fixed anchor motes throughout one floor of a nursing home and mobile units carried by patients. We show how two localization algorithms perform and demonstrate a clear improvement by following a set of simple guidelines to tune the anchor node placement. We show both quantitatively and qualitatively that the results meet the functional and non-functional system requirements.

2024

This paper presents a research and a development of a fingerprint-indoor-positioning system using the Received Signal Strength Indication (RSSI) of a Wireless Sensor Network (WSN). The WSN implementation is based on two different protocol stacks: BitCloud and OpenMAC, a certified ZigBee Compliant Platform (ZCP) and an IEEE 802.15.4 embedded software implementation respectively, both from Atmel, and the system uses two different fingerprint algorithms, Simple and Centroid. A comparative analysis of both algorithms using both protocol stacks implementations have been performed to ascertain the best WSN protocol stack and the best algorithm for positioning purposes.

2024, TDX (Tesis Doctorals en Xarxa)

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2024

This paper presents an analysis of the behaviour of an indoor position system based on fingerprints and IEEE 802.15.4 that has been adapted to be tested in a competition, called EvAAL (Evaluating AAL Systems through Competitive Benchmarking), hold both in Madrid (tests) and Eindhoven (results). The objectives of this analysis are to determine the best algorithm that should have been applied in order to obtain the best results in the competition to use them in other environments. Among the different combinations that can be applied, i.e., the way the signature database is filled in and the algorithm uses to determine the closest location point, the best results are obtained using a global signature database where each signature entry is calculated by the medium of samples signatures database and the closest location is determined by a centroid algorithm with the parameter c set to 1.3. In this way, the error made improves the one obtained in the EvAAL, which is reduced by 100 centime...

2024

In wireless sensor network reliable data transport is one of the most important requirements where different applications have different reliability requirements. The characteristic of wireless sensor network, especially dense deployment, limited processing ability, memory and power supply, provide unique design challenges at transport protocol. A reliable protocol in wireless sensor network must allow data transfer reliably from source to destination with reasonable packet loss. To prolong the lifetime of wireless sensor network efficient transport protocol need to provide congestion control. This paper presents Agent-based Congestion Control Protocol (ACCP) for wireless sensor networks. The traffic rate analysis on each node is based on the priority index and the congestion degree of the node. The parameter such as latency and throughput are investigated. _________________________________________________________________________________________

2024, International Journal of Engineering Trends and Technology (IJETT) - Volume4Issue4- April 2013

Wireless Sensor Network is a type of wireless network which consists of a collection of tiny device called sensor node. Wireless Sensor Network is one of the rapidly developing areas. Applications of Wireless Sensor Network includes remote environmental monitoring, target tracking, etc. Various algorithms are proposed in 2D for location tracking which provides accuracy but in the real world, we require all the three planes for correct estimation and more accuracy in localization. The 2D works on flat terrain but we need to position WSN in harsh terrain also, so we need an algorithm in 3D that provide better accuracy and decrease the error of estimation and provide a real world view also. The goal of our survey is to present the localization techniques of node.

2024, International Journal of Engineering Trends and Technology (IJETT) - Volume4Issue4-

2024

This study was funded by the WSDOT research program led by Rhonda Brooks. The writers are indebted to Casey Kramer, Project Director, Hydraulic Engineer, WSDOT for all the help that he provided during the project. The writers would like also to thank Will Ettema, Dr. Filippo Bressan for their help with the completion of the field work. The interaction with Oregon's RFID Warren Leach has been very informative and constructive. vi

2024

2024, HAL (Le Centre pour la Communication Scientifique Directe)

This demo presents a room-level localization solution built on top of the market leading SmartMesh IP industrial low-power wireless mesh network. Without any changes to the hardware or protocol stack of that product, we re-purpose Blink-a feature designed to allow for mobile nodes-for localization. We demonstrate how we can deploy the resulting localization solution throughout a building by installing an anchor node in each room, and locate the room a mobile tag is in. Initial results indicate that this solution offers over 90% room-level localization accuracy, and at worst adjacent room localization. The unique aspect of it is that the entire network of anchor nodes in battery powered and operates for years on a pair of AA batteries. There are countless applications looking for easily to install and fully battery powered room-level localization, for which our solution, which is production-ready, is ideal.

2024

2024, 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing

2024

Wireless sensor networks (WSN) are networks that deploy hundreds or thousands of wireless sensors in a pre-defined area that can communicate with each other to detect, for example the ambient environment. Each sensor is composed of the four basic elements: transmitting unit, processing unit, power unit and sensing unit. The main task of each sensor is to detect events, perform a restricted set of local data processing tasks and then transmit the data. This technology still in its early stage new researches are being conducted intensively in MAC protocols, network and routing layer, and adaptation into various domains applications. In this proposal, the focus is placed to investigate algorithms in mapping the location of sensor nodes. Knowing the location of the sensor node is critically important; the knowledge of the location of the sensor node that reported a detected event can reduce the time for assistants reaching to the outbreak point. This can potentially save life or can bri...

2024

Network virtualization has become pervasive and is used in many applications. Through the combination of network virtualization and wireless sensor networks, it can greatly improve the multiple applications of traditional wireless sensor networks. However, because of the dynamic reconfiguration of topologies in the physical layer of virtualized sensor networks (VSNs), it requires a mechanism to guarantee the accuracy of estimate values by sensors. In this paper, we focus on the distributed Kalman filter algorithm with dynamic topologies to support this requirement. As one strategy of distributed Kalman filter algorithms, diffusion Kalman filter algorithm has a better performance on the state estimation. However, the existing diffusion Kalman filter algorithms all focus on the fixed topologies. Considering the dynamic topologies in the physical layer of VSNs mentioned above, we present a diffusion Kalman filter algorithm with dynamic topologies (DKFdt). Then, we emphatically derive the theoretical expressions of the mean and mean-square performance. From the expressions, the feasibility of the algorithm is verified. Finally, simulations confirm that the proposed algorithm achieves a greatly improved performance as compared with a noncooperative manner.

2024

The aim of this paper is to emphasize some specific aspects when numerical methods are implemented in Java like involved programming problems, available resources and the possibility to extend the application usage in a distribute... more

2024, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

This paper presents the sensor deployment method to design a RFID sensor network for the mobile robot localization using evolutionary approach. For this purpose, we employ the differential evolution (DE), which is well-known for promising performance. We propose two variation methods, the direct optimization strategy for the maximum usage of initial information intuitively and the full coverage optimization strategy for the dense coverage for the surveillance and the security. In that case, the proper tuning of parameters of DE is essential. We experiment sensor deployment in two maps for providing guidance about parameter tuning. The experimental results show better sensor deployment result according to guided parameter setting. The full coverage optimization strategy also shows proper result using guided parameters from the standard DE case.

2024, EURASIP Journal on Wireless Communications and Networking

Since many range-free localization algorithms depend on only a few anchors and implicit range estimations, they produce poor results. In this article, we propose a distributed range-free algorithm to improve localization accuracy by using one-hop neighbors as well as anchors. When an unknown node knows which nodes it can directly communicate with, but does not know how far they are exactly placed, the node should have a location having the average distance to all neighbors since the location minimizes the sum of squares of hop distance errors. In the proposed algorithm, each node initializes its location using the information of anchors and updates it based on mass spring method and Kalman filtering with the location estimates of one-hop neighbors until the equilibrium is achieved. Subsequently, the network has the shape of isotropic graph with minimized variance of links between one-hop neighbors. We evaluate our algorithm and compare it with other range-free algorithms through simulations under varying node density, anchor ratio, and node deployment method.

2024, International Journal of Distributed Sensor Networks

In range-free localization scheme of wireless sensor networks, estimating the distance to the anchor nodes having the actual location is common to compute the position of unknown node. Since the range-free scheme is based on the topology information, the accuracy of distance estimation is considerably affected by node density or node deployment. In this paper, we propose a geometric range-free localization algorithm which estimates the unknown positions geometrically by topological information without considering the distance estimation. To achieve this, we propose an optimal anchor node selection algorithm which selects the anchor nodes connected topologically well for the geometrical location estimation. Simulation results show that the proposed algorithm offers considerably an improved performance compared to the other existing studies.

2024, Wireless Communications and Mobile Computing

Wireless networks include a set of nodes which are connected to one another via wireless links for communication purposes. Wireless sensor networks (WSN) are a type of wireless network, which utilizes sensor nodes to collect and communicate data. Node localization is a challenging problem in WSN which intends to determine the geographical coordinates of the sensors in WSN. It can be considered an optimization problem and can be addressed via metaheuristic algorithms. This study introduces an elite oppositional farmland fertility optimization-based node localization method for radio communication networks, called EOFFO-NLWN technique. It is the goal of the proposed EOFFO-NLWN technique to locate unknown nodes in the network by using anchor nodes as a starting point. As a result of merging the principles of elite oppositional-based learning (EOBL) and the agricultural fertility optimization algorithm (FFO), we have developed the EOFFO-NLWN approach, which is described in detail below....

2024

This paper addresses the problem of controlling mobile sensing systems to improve the accuracy and efficiency of gathering information autonomously. It applies to scenarios such as environmental monitoring, search and rescue, surveillance and reconnaissance, and simultaneous localization and mapping (SLAM). A multi-sensor active information acquisition problem, capturing the common characteristics of these scenarios, is formulated. The goal is to design sensor control policies which minimize the entropy of the estimation task, conditioned on the future measurements. First, we provide a non-greedy centralized solution, which is computationally fast, since it exploits linearized sensing models, and memory efficient, since it exploits sparsity in the environment model. Next, we decentralize the control task to obtain linear complexity in the number of sensors and provide suboptimality guarantees. Finally, our algorithms are applied to the multi-robot active SLAM problem to enable a decentralized nonmyopic solution that exploits sparsity in the planning process.

2024, IEEE Transactions on Instrumentation and Measurement

In this paper, a new approach is proposed to estimate the location of a sensor in a wireless sensor network. For the estimation, only a few anchor nodes with known locations and received signal strength (RSS) indicator (RSSI) are needed. It is well known that the RSS reduces with increasing distance between the transceivers following a nonlinear path loss model. Most published works determine these parameters offline. This often yields limited estimation accuracy due to high variance of RSSI measurements. To improve the estimation accuracy, the parameters are estimated together with the unknown node's location in real time in this paper. To optimize the results, a new particle swarm optimization with log-barrier approach is proposed. Both simulation and experimental results show that the proposed scheme performs well as compared with some existing schemes.

2024, Zenodo (CERN European Organization for Nuclear Research)

A large number of inexpensive, small sensors make up a wireless sensor network. The collection and transmission of data is one of the crucial functions of a sensor network. In the greater part of the applications, it is of much interest to figure out the area of the information. Localization methods can be used to obtain this kind of information. Therefore, node localization is very important when using localization algorithms to determine the position of a node. As a result, WSN node localization emerges as one of the primary obstacles. The localization schemes can be broadly divided into two groups based on range measurements, such as: range based and range free plans. Range-based localization techniques cannot be used due to the sensing node's hardware limitations and high cost. Since coarse accuracy is sufficient for most sensor network applications, range-free schemes are being considered an alternative. The performances and accuracy of the range-free algorithms were tested with the application of MATLAB 2017a. The results demonstrated that the amorphous algorithm has the lowest localization error in most cases in comparison to the performance of these four algorithms. Likewise, results demonstrated amorphous, and DV-hop algorithms have 100% coverage rate in every situation that were tested.

2024, Digital Communications and Networks

The design of resilient networks is of utmost importance today, owing to the wide range of safety-critical applications. Resilient networks try to guarantee an acceptable level of Quality of Service (QoS), even in cases of challenges and faults in the system. The causes of obstruction in normal system operation range from simple misconfiguration, hardware failures, and software failures to intended attacks and natural disasters. To enable the resilience of a network, it is important to identify the causes of faults and challenges, and to take necessary measures to protect the services from being affected. Considering the massive increase in the number of applications running on the Internet, and the significant societal and economic consequences of their outages, this special issue offers an overview of the state-of-the-art technology and the research advances on issues, challenges, and potential solutions for modeling and designing resilient networks. We are excited to have received 24 submissions in total for this special issue from the authors of the 4th International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2016) as well as extended works from independent authors responding to our open call. After a strict peer review and revision process, only seven articles were selected to be featured in this special issue. The selected papers cover various aspects of resilient networks, namely, QoS routing protocols ([1,2]), network security ([3]), fault recovery ([4,5]), and effective service selection ([6,7]). The first two articles highlight the development of QoS routing protocols for efficient communication. In the first article, titled "QoS aware routing and wavelength allocation in optical burst switching networks using differential evolution optimization" [1], the authors present a QoSaware routing and wavelength allocation (RWA) technique for burst switching in optical burst-switching networks. The authors model the problem as a bi-objective integer linear programming (ILP) problem. The goals are to minimize both the number of wavelengths used and the number of hops traversed by the optical signal, from source to a given destination. The authors propose a novel approach to solve the minimization problem using differential evolution, which outperforms the shortest-path routing algorithm. The second article in this category, titled "Trade-off between accuracy, cost and QoS using Beacon on Demand strategy and Kalman filtering over VANET" [2], presents an improved Greedy Perimeter Stateless Routing (GPSR) protocol for VANET, in which the vehicles can estimate the positions of their neighbors using a Kalman filter algorithm. This protocol reduces the frequency of beacon exchanges compared with that of the broadcasting periodic beaconing used in GPSR. The proposed protocol is supplemented with a "Beacon on Demand" process, through which a node can explicitly discover its neighborhood whenever required. The packet delivery ratio, routing cost,

2024

HIGH-PERFORMANCE PROCESSING OF CONTINUOUS UNCERTAIN DATA

2024

Brain-computer interface (BCI) is a system to translate humans thoughts into commands. For electroencephalography (EEG) based BCI, motor imagery is considered as one of the most effective ways. This paper presents a method for classifying EEG during motor-imagery by the combination of well-known common spatial pattern (CSP) with so-called multivariate empirical mode decomposition (MEMD), which is effectively suitable for processing of multichannel signals of EEG. In the proposed method, the EEG signal is decomposed into intrinsic mode functions (IMF) using the MEMD. Different from EMD, the number of IMF is the same in each channel. Then by removing some of the IMFs, the reconstructed signal can carry more useful information than the original signal. Based on the MEMD, weights of CSP are found. By off-line simulation, the use of MEMD in CSP has shown to perform well in the application to the classification of EEG signals.

2024, Digital Communications and Networks

Wireless sensor networks are susceptible to failures of its nodes and links due to various physical or computational reasons. Some physical reasons include very high temperature, heavy load over a node, heavy rain. Computational reasons could be third party intrusive attack, communication conflicts or congestions. Automated fault diagnosis has been a well-studied problem in the research community. In this paper, we present an automated fault diagnosis model that can diagnose multiple types of faults in the category of hard faults and soft faults. Our proposed model implements a feed-forward neural network that is trained with a hybrid meta-heuristic algorithm which combines the principles of exploration and exploitation of the search space. The proposed methodology consists of different phases such as clustering phase, fault detection and classification phase, and decision and diagnosis phase. The implemented methodology can diagnose composite faults such as hard permanent, soft permanent, intermittent, and transient fault for sensor nodes as well as for links. The proposed implementation can also classify different types of faulty behavior for both sensor nodes and links in the network. We present the obtained theoretical results and computational complexity of the implemented model for this particular study $ Fully documented templates are available in the elsarticle package on CTAN.

2024

Ambient Assisted Living is based on a set of technologies with the aim to provide an enhanced support to people's daily life. One important field deals with the offer of new solutions for healthcare. Those solutions intend to improve the population quality of life and reduce costs associated with healthcare. Before that happens, new platforms, hardware and software, must be available in order to acquire and store the required signals, to process and extract information from those signals, and to detect a set of features required to fire alarms and/or electronic assistance. This paper presents a platform (hardware and software) that was designed to acquire data from a subject, or from a device, and send it to a remote hub. It was designed taking into account its size, power autonomy, and quality of service, and is able to perform the required monitoring tasks, at least, for one day.