1,074 research outputs found

    Dead Reckoning Localization Technique for Mobile Wireless Sensor Networks

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    Localization in wireless sensor networks not only provides a node with its geographical location but also a basic requirement for other applications such as geographical routing. Although a rich literature is available for localization in static WSN, not enough work is done for mobile WSNs, owing to the complexity due to node mobility. Most of the existing techniques for localization in mobile WSNs uses Monte-Carlo localization, which is not only time-consuming but also memory intensive. They, consider either the unknown nodes or anchor nodes to be static. In this paper, we propose a technique called Dead Reckoning Localization for mobile WSNs. In the proposed technique all nodes (unknown nodes as well as anchor nodes) are mobile. Localization in DRLMSN is done at discrete time intervals called checkpoints. Unknown nodes are localized for the first time using three anchor nodes. For their subsequent localizations, only two anchor nodes are used. The proposed technique estimates two possible locations of a node Using Bezouts theorem. A dead reckoning approach is used to select one of the two estimated locations. We have evaluated DRLMSN through simulation using Castalia simulator, and is compared with a similar technique called RSS-MCL proposed by Wang and Zhu .Comment: Journal Paper, IET Wireless Sensor Systems, 201

    Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review

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    The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of stateof-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages and disadvantages. The similarities and differences of each scheme are investigated on the basis of significant parameters, namely, localization accuracy, computational cost, communication cost, and number of samples. We discuss the challenges and direction of the future research work for each parameter

    Sensor Network-based and User-friendly User Location Discovery for Future Smart Homes

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    User location is crucial context information for future smart homes where a lot of location based services will be proposed. This location necessarily means that User Location Discovery (ULD) will play an important role in future smart homes. Concerns about privacy and the need to carry a mobile or a tag device within a smart home currently makes conventional ULD systems uncomfortable for users. Future smart homes will need a ULD system to consider these challenges. This paper addresses to design such a ULD system for context-aware services in future smart homes stressing on the following challenges: (i) users’ privacy, (ii) device/tag-free, and (iii) fault tolerance and accuracy. On the other hand, emerging new technologies such as Internet of Things, embedded systems, intelligent devices and machine-to-machine communication are penetrating into our daily life with more and more sensors available for use in our homes. Considering this opportunity, we propose a ULD system that is capitalizing on the prevalence of sensors or home while satisfying the aforementioned challenges. The proposed sensor network-based and user-friendly ULD system relies on different types of cheap sensors as well as a context broker with a fuzzy-based decision maker. The context broker receives context information from different types of sensors and evaluates that data using the fuzzy set theory. We demonstrate the performance of the proposed system by illustrating a use case, utilizing both an analytical model and simulation

    Locating Emergency Responders using Mobile Wireless Sensor Networks

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    ABSTRACT Emergency response in disaster management using wireless sensor networks has recently become an interest of many researchers in the world. This interest comes from the growing number of disasters and crisis (natural or man-made) affecting millions of lives and the easy-use of new and cheap technologies. This paper details another application of WSN in the post disaster scenario and comes up with an algorithm for localization of sensors attached to mobile responders (firefighters, policemen, first aid agents, emergency nurses, etc) while assisted by a mobile vehicle (fire truck, police car, or aerial vehicle like helicopters) called mobile anchor, sent to supervise the rescue operation. This solution is very efficient and rapidly deployable since no pre-installed infrastructure is needed. Also, there is no need to equip each sensor with a GPS receiver which is very costly and may increase the sensor volume. The proposed technique is based on the prediction of the rescuers velocities and directions considering previous position estimations. The evaluation of our solution shows that our technique takes benefit from prediction in a more effective manner than previous solutions. The simulation results show that our algorithm outperforms conventional Monte Carlo localization schemes by decreasing estimation errors with more than 50%

    Wireless Sensor Networks for Underwater Localization: A Survey

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    Autonomous Underwater Vehicles (AUVs) have widely deployed in marine investigation and ocean exploration in recent years. As the fundamental information, their position information is not only for data validity but also for many real-world applications. Therefore, it is critical for the AUV to have the underwater localization capability. This report is mainly devoted to outline the recent advance- ment of Wireless Sensor Networks (WSN) based underwater localization. Several classic architectures designed for Underwater Acoustic Sensor Network (UASN) are brie y introduced. Acoustic propa- gation and channel models are described and several ranging techniques are then explained. Many state-of-the-art underwater localization algorithms are introduced, followed by the outline of some existing underwater localization systems

    Efficient Range-Free Monte-Carlo-Localization for Mobile Wireless Sensor Networks

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    Das Hauptproblem von Lokalisierungsalgorithmen für WSNs basierend auf Ankerknoten ist die Abhängigkeit von diesen. Mobilität im Netzwerk kann zu Topologien führen, in denen einzelne Knoten oder ganze Teile des Netzwerks temporär von allen Ankerknoten isoliert werden. In diesen Fällen ist keine weitere Lokalisierung möglich. Dies wirkt sich primär auf den Lokalisierungsfehler aus, der in diesen Fällen stark ansteigt. Des weiteren haben Betreiber von Sensornetzwerken Interesse daran, die Anzahl der kosten- und wartungsintensiveren Ankerknoten auf ein Minimum zu reduzieren. Dies verstärkt zusätzlich das Problem von nicht verfügbaren Ankerknoten während des Netzwerkbetriebs. In dieser Arbeit werden zunächst die Vor- und Nachteile der beiden großen Hauptkategorien von Lokalisierungsalgorithmen (range-based und range-free Verfahren) diskutiert und eine Studie eines oft für range-based Lokalisierung genutzten Distanzbestimmungsverfahren mit Hilfe des RSSI vorgestellt. Danach werden zwei neue Varianten für ein bekanntes range-free Lokalisierungsverfahren mit Namen MCL eingeführt. Beide haben zum Ziel das Problem der temporär nicht verfügbaren Ankerknoten zu lösen, bedienen sich dabei aber unterschiedlicher Mittel. SA-MCL nutzt ein dead reckoning Verfahren, um die Positionsschätzung vom letzten bekannten Standort weiter zu führen. Dies geschieht mit Hilfe von zusätzlichen Sensorinformationen, die von einem elektronischen Kompass und einem Beschleunigungsmesser zur Verfügung gestellt werden. PO-MCL hingegen nutzt das Mobilitätsverhalten von einigen Anwendungen in Sensornetzwerken aus, bei denen sich alle Knoten primär auf einer festen Anzahl von Pfaden bewegen, um den Lokalisierungsprozess zu verbessern. Beide Methoden werden durch detaillierte Netzwerksimulationen evaluiert. Im Fall von SA-MCL wird außerdem eine Implementierung auf echter Hardware vorgestellt und eine Feldstudie in einem mobilen Sensornetzwerk durchgeführt. Aus den Ergebnissen ist zu sehen, dass der Lokalisierungsfehler in Situationen mit niedriger Ankerknotendichte im Fall von SA-MCL um bis zu 60% reduziert werden kann, beziehungsweise um bis zu 50% im Fall von PO-MCL.

    Localisation in wireless sensor networks for disaster recovery and rescuing in built environments

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    A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyProgress in micro-electromechanical systems (MEMS) and radio frequency (RF) technology has fostered the development of wireless sensor networks (WSNs). Different from traditional networks, WSNs are data-centric, self-configuring and self-healing. Although WSNs have been successfully applied in built environments (e.g. security and services in smart homes), their applications and benefits have not been fully explored in areas such as disaster recovery and rescuing. There are issues related to self-localisation as well as practical constraints to be taken into account. The current state-of-the art communication technologies used in disaster scenarios are challenged by various limitations (e.g. the uncertainty of RSS). Localisation in WSNs (location sensing) is a challenging problem, especially in disaster environments and there is a need for technological developments in order to cater to disaster conditions. This research seeks to design and develop novel localisation algorithms using WSNs to overcome the limitations in existing techniques. A novel probabilistic fuzzy logic based range-free localisation algorithm (PFRL) is devised to solve localisation problems for WSNs. Simulation results show that the proposed algorithm performs better than other range free localisation algorithms (namely DVhop localisation, Centroid localisation and Amorphous localisation) in terms of localisation accuracy by 15-30% with various numbers of anchors and degrees of radio propagation irregularity. In disaster scenarios, for example, if WSNs are applied to sense fire hazards in building, wireless sensor nodes will be equipped on different floors. To this end, PFRL has been extended to solve sensor localisation problems in 3D space. Computational results show that the 3D localisation algorithm provides better localisation accuracy when varying the system parameters with different communication/deployment models. PFRL is further developed by applying dynamic distance measurement updates among the moving sensors in a disaster environment. Simulation results indicate that the new method scales very well

    Anchor-Free Localization in Mixed Wireless Sensor Network Systems

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    Recent technological advances have fostered the emergence of Wireless Sensor Networks (WSNs), which consist of tiny, wireless, battery-powered nodes that are expected to revolutionize the ways in which we understand and construct complex physical systems. A fundamental property needed to use and maintain these WSNs is ``localization\u27\u27, which allows the establishment of spatial relationships among nodes over time. This dissertation presents a series of Geographic Distributed Localization (GDL) algorithms for mixed WSNs, in which both static and mobile nodes can coexist. The GDL algorithms provide a series of useful methods for localization in mixed WSNs. First, GDL provides an approximation called ``hop-coordinates\u27\u27, which improves the accuracy of both hop-counting and connectivity-based measurement techniques. Second, GDL utilizes a distributed algorithm to compute the locations of all nodes in static networks with the help of the hop-coordinates approximation. Third, GDL integrates a sensor component into this localization paradigm for possible mobility and as a result allows for a more complex deployment of WSNs as well as lower costs. In addition, the development of GDL incorporated the possibility of manipulated communications, such as wormhole attacks. Simulations show that such a localization system can provide fundamental support for security by detecting and localizing wormhole attacks. Although several localization techniques have been proposed in the past few years, none currently satisfies our requirements to provide an accurate, efficient and reliable localization for mixed WSNs. The contributions of this dissertation are: (1) our measurement technique achieves better accuracy both in measurement and localization than other methods; (2) our method significantly improves the efficiency of localization in updating location in mixed WSNs by incorporating sensors into the method; (3) our method can detect and locate the communication that has been manipulated by a wormhole in a network without relying on a central server

    Z-path trajectory mechanism for mobile beacon-assisted localization in wireless sensor networks

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    A wireless sensor network consists of many sensors that communicate wirelessly to monitor a physical region. In many applications such as warning systems or healthcare services, it is necessary to enhance the captured data with location information. Determining the coordinates of the randomly deployed sensors is known as the problem of localization. A promising solution for statically deployed sensors is to benefit from a mobile beacon-assisted localization. The main challenge is planning an optimum path for the mobile beacon to ensure the full coverage, increase the accuracy of the estimated position and decrease the required time for localization of resource-constrained sensors. So, this research aims at developing a superior trajectory mechanism for mobile beacon-assisted localization to help unknown sensors to efficiently localize themselves. To achieve this purpose; first, a novel trajectory named Z-path is proposed to guarantee fully localized deployed sensors with higher precision since the path reduces collinear beacon positions and promises shorter localization time; second, Z-path transmission power adjustment scheme named Zpower is developed to dynamically and optimally adjust the transmission power for a reliable transmission while conserving the energy consumption for localization by mobile beacon and unknown sensors; third, Z-path obstacle-handling trajectory mechanism is designed to improve the effectiveness of the proposed path toward obstacles which obstruct the path. Finally, the proposed Z-path obstacle handling mechanism is integrated with the developed power adjustment scheme to improve the energy efficiency of the designed obstacle tolerance mechanism. The performance of the proposed trajectory is evaluated by comparing the efficiency with five benchmark trajectories in terms of localization success, accuracy, energy efficiency, time and ineffective position rate, which is a newly introduced metric by this research to measure the collinearity of the trajectories. Simulation results show that Z-path has successfully localized all 250 deployed sensors with higher precision by at least 5.88% improvement than Localization with a Mobile Anchor based on Trilateration (LMAT) trajectory and 58% improvement than random way point. It also serves as a benchmark path with 93 ineffective positions per node localization as compared with LMAT as a second efficient path by 100 collinear positions and faster trajectory for localization. Furthermore, results revealed that Z-power accomplishes better performance in terms of energy consumption as an average 34% for unknown sensors and 25% for mobile beacon than Z-path. In case of obstacle tolerance mechanism, it ensures higher localization performance in terms of accuracy, time and success around 37.5%, 13% and 11% respectively, as compared to Z-path at the presence of obstacles. The handling mechanism integrated with the power control scheme has reduced energy consumption and improved ineffective position rate compared with Z-path handling trajectory by 35.7% and 54.4%, respectively
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