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1
EN
Wireless Sensor Networks (WSN) are one of important tools for controlling and collecting data in the internet of things (IoT). For wireless sensor network design, power consumption and network lifetime functions are important for maintenance. Therefore, low-cost innovations that could reduce energy consumption and extend the network lifetime are essential in development of next-generation WSN. In this research, a hexagonal equation model for WSN was utilized to reduce energy consumption. The design was generated in an area of 35m  35m and the number of sensor nodes was 30, 40, 50, 60, 70, 80, 90, and 100 loads, respectively. The results of energy efficiency were compared to Developed Distributed EnergyEfficient Clustering (DDEEC) and Distributed Energy-Efficient Clustering algorithm (DEEC). The results showed that the DDEEC method performed better than the DEEC method in terms of the power dissipation on the nodes 30-100 loads.
PL
Bezprzewodowe sieci czujników (WSN) są jednym z ważnych narzędzi do kontrolowania i gromadzenia danych w Internecie rzeczy (IoT). W przypadku projektowania sieci czujników bezprzewodowych zużycie energii i funkcje związane z okresem eksploatacji sieci są ważne dla konserwacji. Dlatego tanie innowacje, które mogłyby zmniejszyć zużycie energii i wydłużyć żywotność sieci, są niezbędne w rozwoju sieci WSN nowej generacji. W tym badaniu wykorzystano model równania heksagonalnego dla WSN w celu zmniejszenia zużycia energii. Projekt został wygenerowany na obszarze 35m  35m, a liczba węzłów sensorów wynosiła odpowiednio 30, 40, 50, 60, 70, 80, 90 i 100 obciążeń. Wyniki efektywności energetycznej porównano z algorytmem Developed Distributed Energy-Efficient Clustering (DDEEC) i Distributed Energy-Efficient Clustering (DEEC). Wyniki pokazały, że metoda DDEEC wypadła lepiej niż metoda DEEC pod względem rozpraszania mocy na węzłach 30-100 obciążeń.
EN
Wireless Sensor Networks (WSN) acquired a lot of attention due to their widespread use in monitoring hostile environments, critical surveillance and security applications. In these applications, usage of wireless terminals also has grown significantly. Grouping of Sensor Nodes (SN) is called clustering and these sensor nodes are burdened by the exchange of messages caused due to successive and recurring re-clustering, which results in power loss. Since most of the SNs are fitted with nonrechargeable batteries, currently researchers have been concentrating their efforts on enhancing the longevity of these nodes. For battery constrained WSN concerns, the clustering mechanism has emerged as a desirable subject since it is predominantly good at conserving the resources especially energy for network activities. This proposed work addresses the problem of load balancing and Cluster Head (CH) selection in cluster with minimum energy expenditure. So here, we propose hybrid method in which cluster formation is done using unsupervised machine learning based kmeans algorithm and Fuzzy-logic approach for CH selection.
EN
Wireless Sensor Network (WSN) technology has grown in importance in recent years. All WSN implementations need secure data transmission between sensor nodes and base stations. Sensor node attacks introduce new threats to the WSN. As a result, an appropriate Intrusion Detection System (IDS) is required in WSN for defending against security attacks and detecting attacks on sensor nodes. In this study, we use the Routing Protocol for Low Power and Lossy Networks (RPL) for addressing security services in WSN by identifying IDS with a network size of more or less 20 nodes and introducing 10% malicious nodes. The method described above is used on Cooja in the VMware virtual machine Workstation with the InstantContiki2.7 operating system. To track the movement of nodes, find network attacks, and spot dropped packets during IDS in WSN, an algorithm is implemented in the Network Simulator (NS2) using the Ad-hoc On-Demand Distance Vector (AODV) protocol in the Linux operating system.
EN
Over the past two decades, numerous research projects have concentrated on cognitive radio wireless sensor networks (CR-WSNs) and their benefits. To tackle the problem of energy and spectrum shortfall in CR-WSNs, this research proposes an underpinning decode-&-forward (DF) relaying technique. Using the suggested time-slot architecture (TSA), this technique harvests energy from a multi-antenna power beam (PB) and delivers source information to the target utilizing energy-constrained secondary source and relay nodes. The study considers three proposed relay selection schemes: enhanced hybrid partial relay selection (E-HPRS), conventional opportunistic relay selection (C-ORS), and leading opportunistic relay selection (L-ORS). We present evidence for the sustainability of the suggested methods by examining the outage probability (OP) and throughput (TPT) under multiple primary users (PUs). These systems leverage time switching (TS) receiver design to increase end-to-end performance while taking into account the maximum interference constraint and transceiver hardware inadequacies. In order to assess the efficacy of the proposed methods, we derive the exact and asymptotic closed-form equations for OP and TPT & develop an understanding to learn how they affect the overall performance all across the Rayleigh fading channel. The results show that OP of the L-ORS protocol is 16% better than C-ORS and 75% better than E-HPRS in terms of transmitting SNR. The OP of L-ORS is 30% better than C-ORS and 55% better than E-HPRS in terms of hardware inadequacies at the destination. The L-ORS technique outperforms C-ORS and E-HPRS in terms of TPT by 4% and 11%, respectively.
PL
Badania nad topologią bezprzewodowych sieci sensorowych (WSN) koncentrują się głównie na modelowaniu i analizie metod optymalizacji struktury połączeń. Tego typu podejście jest jednak rzadko wykorzystywane przez projektantów sieci, a powstające systemy czujników w środowiskach miejskich często odbiegają od wzorców proponowanych w literaturze i dostępnych modelach. Zakłada się, że otwarty dostęp do rzeczywistych danych pochodzących z różnych typów urządzeń pozwoli zrozumieć naturę tych danych, a także wyodrębnić i rozwiązać problemy występujące w heterogenicznych sieciach. Analizowanie topologii takich sieci i diagnozowanie problemów powinno zatem opierać się na danych uzyskanych z rzeczywistych sieci. Dzięki takiemu podejściu możliwe jest zrozumienie zmian w typologii sieci oraz identyfikacja problemów w heterogenicznych sieciach bezprzewodowych. W artykule przedstawiono wybrane najważniejsze i zarazem aktualne tematy badawcze związane z miejskimi sieciami czujników. Zaprezentowano również koncepcję modelowania sieci w oparciu o publicznie dostępne dane o położeniu geograficznym węzłów w czasie rzeczywistym.
PL
W artykule opisano nową metodę lokalizowania obiektów dla szerokiej gamy zastosowań, w tym Internetu Rzeczy. Zaproponowana metoda umożliwia estymację położenia i orientacji obiektu na płaszczyźnie lub w przestrzeni, również będącego w spoczynku, za pomocą sygnałów lokalizacyjnych wysyłanych jednocześnie z dwóch nadajników umieszczonych na obiekcie w znanej odległości od siebie. Przedstawiono matematyczną analizę metody oraz wyniki badań symulacyjnych efektywności pracy zaproponowanej metody.
EN
The paper proposes a new method of locating objects for all kinds of applications, including the Internet of Things. The proposed method enables the estimation of the position and orientation of an object on a plane or in space, also at rest, by means of location signals sent simultaneously from two transmitters placed on the object at a known distance from each other. The mathematical analysis of the method and the results of simulation tests of the effectiveness of the proposed method are presented.
EN
With the growth of wireless sensor network (WSN) technologies, the applications of IoT-based WSNs allow the interconnection of smart objects or sensors through the Internet. However, energy constraint is a major obstacle in WSN, which directly affects the lifespan of the network. Hence, many researchers have focused on how to program routing protocols to maximize energy conservation in WSNs. The clustering mechanism is demonstrated that separating the network into clusters may significantly decrease energy consumption. In this paper, we propose distributed tree-based clustering routing protocol for IoT applications (EE-DTC). In order to enhance efficient energy, EE-DTC chooses cluster head nodes based on the remaining energy, the location, and the density of nodes. In addition, to lengthen the network lifespan, we create multi-hop routes with short communication links intra-clusters by building the minimum spanning tree using the Kruskal algorithm. Our experiment results show that the performance of EE-DTC overcomes the TBC and LEACH-VA protocols in terms of increasing network lifespan, reducing energy consumption, and improving efficient energy.
EN
Recent rapid penetration of Internet of Things (IoT) in various fields such as smart homes, healthcare, and industrial applications has raised new challenges on the QoS requirements including data prioritization and energy saving. In IoT networks, data is heterogeneous and varies in a wide range of categories and urgency. More critical data must be served more quickly and reliably than regular data. In order to deal with crucial issues effectively and improve the performance of wireless sensor networks in IoT, we propose an efficient Backoff Priority-based Medium Access Control (BoP-MAC) scheme that supports multiple priority data and exploits the use of backoff mechanism. In our proposed solution, data priority is utilized to properly resize the backoff window at the MAC layer to ensure that high-priority data are transferred earlier and more reliably. Numerical simulations are used on OMNeT++ to verify the efficiency of our proposed BoP-MAC protocol in comparison with that of a notably conventional MAC protocol called Timeout Multi-priority-based MAC (TMPQ-MAC) protocol. The attained experimental results demonstrate that our developed BoP-MAC protocol outperforms the comparable conventional one and becomes more efficient for large-scale wireless sensor networks. It can effectively cope with various data priorities and enhance significantly the overall performance, in terms of latency, energy consumption, and packet success ratio, of the network.
EN
How to use efficient energy in wireless sensor networks (WSN) is one of the major challenges due to limited energy batteries and computation capacity. Therefore, in this paper, we propose combining a chain-base routing scheme and data fusion sensor information (CRSDF for short). CRSDF contains two major works: Firstly, the chain-based routing method is applied to connect sensor nodes into a chain in which each node transmits only with the nearest neighbor using the remaining energy and distance of nodes as standard parameters to determine which node will be selected the chain leader, secondly, we fuse and compress one or more data packets to generate a result packet with small size base on the Slepian-Wolf and Dempster-Shafer theory. The simulation results exhibit that the energy efficiency of our proposed protocol can be improved by 40\%, 20\%, and 15\% compared to low-energy adaptive clustering hierarchy (LEACH), power-efficient gathering in sensor information system (PEGASIS), and an improved energy-efficient PEGASIS-Based protocol, respectively.
10
Content available remote Ant colony based coverage optimization in wireless sensor networks
EN
Maximizing the covered area of wireless sensor networks while keeping the connectivity between the nodes is one of the challenging tasks in wireless sensor networks deployments. In this paper we propose an ant colony-based method for the problem of sensor nodes deployment to maximize the coverage area. We model sensor locations as a graph and use an adapted ant colony optimization-based method to find the best places for each sensor node. To keep the connectivity of the sensor network, every sensor must be covered by the other sensors; this is a hard constraint that is applied to the cost function as a penalty. The proposed algorithm is evaluated with different number of sensor nodes and sensing ranges. The simulation results showed that increasing the number of iterations in the algorithm generates better coverage ratio with the same number of nodes.
EN
We introduce a wireless sensor network (WSN) architecture intended for massive deployments in custom applications where the primary goal is the collection of low-volume (e.g., telemetric) data possibly augmented with spontaneous special events, like alerts or alarms. The network is built of inexpensive, small-footprint, energy-frugal, possibly mobile nodes running reactive programs and self-organizing themselves into resilient distributed systems in a manner embracing the limited capabilities of the devices as well as the unreliable nature of ad-hoc wireless communication. We propose and elaborate on a holistic approach to constructing complete WSN applications. Our approach incorporates a certain unified programming and communication paradigm. In addition to producing small, energy-efficient, self-documenting and reliable programs for ultra-small-footprint motes, that paradigm enables authoritative virtual execution of complete application, thus facilitating their rapid development, testing, augmentation and modification.
EN
Due to the severe damages of nuclear accidents, there is still an urgent need to develop efficient radiation detection wireless sensor networks (RDWSNs) that precisely monitor irregular radioactivity. It should take actions that mitigate the severe costs of accidental radiation leakage, especially around nuclear sites that are the primary sources of electric power and many health and industrial applications. Recently, leveraging machine learning (ML) algorithms to RDWSNs is a promising solution due to its several pros, such as online learning and self-decision making. This paper addresses novel and efficient ML-based RDWSNs that utilize millimeter waves (mmWaves) to meet future network requirements. Specifically, we leverage an online learning multi-armed bandit (MAB) algorithm called Thomson sampling (TS) to a 5G enabled RDWSN to efficiently forward the measured radiation levels of the distributed radiation sensors within the monitoring area. The utilized sensor nodes are lightweight smart radiation sensors that are mounted on mobile devices and measure radiation levels using software applications installed in these mobiles. Moreover, a battery aware TS (BATS) algorithm is proposed to efficiently forward the sensed radiation levels to the fusion decision center. BA-TS reflects the remaining battery of each mobile device to prolong the network lifetime. Simulation results ensure the proposed BA-TS algorithm’s efficiency regards throughput and network lifetime over TS and exhaustive search method.
PL
W artykule opisano innowacyjną metodę lokalizowania obiektów dla potrzeb Internetu rzeczy (IoT). Przedstawiono matematyczną analizę metody. Opisano również wyniki kompleksowych badań symulacyjnych efektywności pracy zaproponowanej metody dla wybranych parametrów radiowej sieci sensorowej.
EN
The paper proposes an innovative method of locating objects for the Internet of Things (IoT). The mathematical analysis of the method is presented. The results of complex simulation studies on the efficiency of the proposed method for various selected system parameters of the sensor network are described.
EN
The paper presents a circuit structure that can be used for powering an IoT (Internet of Things) sensor node and that can use energy just from its surroundings. The main advantage of the presented solution is its very low cost that allows mass applicability e.g. in the IoT smart grids and ubiquitous sensors. It is intended for energy sources that can provide enough voltage but that can provide only low currents such as piezoelectric transducers or small photovoltaic panels (PV) under indoor light conditions. The circuit is able to accumulate energy in a capacitor until a certain level and then to pass it to the load. The presented circuit exhibits similar functionality to a commercially available EH300 energy harvester (EH). The paper compares electrical properties of the presented circuit and the EH300 device, their form factors and costs. The EH circuit’s performance is tested together with an LTC3531 buck-boost DC/DC converter which can provide constant voltage for the following electronics. The paper provides guidelines for selecting an optimal capacity of the storage capacitor. The functionality of the solution presented is demonstrated in a sensor node that periodically transmits measured data to the base station using just the power from the PV panel or the piezoelectric generator. The presented harvester and powering circuit are compact part of the sensor node’s electronics but they can be also realized as an external powering module to be added to existing solutions.
EN
Design of the MAC protocol is crucial in all wireless sensor networks (WSNs) due to its influence on the performance of the transceiver, i.e. the most energy-consuming component of each sensor node. A mechanism known as “carrier sense multiple access with collision avoidance” (CSMA/CA) is used for accessing the wireless channel in the IEEE 802.15.4 standard-based MAC protocol in order to avoid collisions between the network’s communicating nodes. CSMA/CA relies on two clear channel assessments (CCA=2) for checking the status of the channel. In this paper, we develop an additional CCA algorithm for the two scenarios encountered in star topology-enabled WSNs. Next, we investigate the impact of an additional clear channel assessment (CCA=3) on performance in IEEE 802.15.4. We develop a Markov chain model for the proposed methodology, and validate it using Matlab. Simulation results show that there is a significant improvement of performance metrics in the IEEE 802.15.4 standard-based MAC protocol with an additional CCA.
EN
Wireless sensor networks are typically operated on batteries. Therefore, in order to prolong network lifetime, an energy efficient routing algorithm is required. In this paper, an energy-aware routing protocol for the co-operative MIMO scheme in WSNs (EARPC) is presented. It is based on an improved cluster head selection method that considers the remaining energy level of a node and recent energy consumption of all nodes. This means that sensor nodes with lower energy levels are less likely to be chosen as cluster heads. Next, based on the cooperative node selection in each cluster, a virtual MIMO array is created, reducing uneven distribution of clusters. Simulation results show that the proposed routing protocol may reduce energy consumption and improve network lifetime compared with the LEACH protocol.
EN
Wireless Sensor Network finds its extensive use in healthcare applications for the transfer of time-critical data through wireless connectivity. The primary cause of network failure is the transfer of time-critical multimedia data. The article presents a new dfferentiated service modelsupported (DSM) cluster-based routing in wireless sensor networks (WSNs) that overcomes the above issue. DSM prioritizes the transfer of dfferent flow types based on packet type and packet size. The employment of computational offlading minimizes delay for critical and small-sized data packets and by carrying out data reduction of large-sized packets at proxy server. It outperforms the existing protocols in terms of energy efficiency, throughput, and reliability by prioritizing the transfer of time-critical health application data.
EN
The 6TiSCH communication stack enables IPv6 networking over the TSCH (Time Slotted Channel Hopping) mode of operation defined in IEEE 802.15.4. Lately it became an attractive solution for Low power and Lossy Networks (LLNs), suitable for Industrial Internet (IIoT) applications. This article introduces a credible energy consumption model for the 6TiSCH network nodes, operating in the 863-870 MHz band. It presents the analysis leading to the construction of the model as well as verification through experimental measurements which showed 98% accuracy in determining power consumption for two different network topologies. The article includes reliable battery lifetime predictions for transit and leaf nodes along with other parametric study results.
PL
Stężenia i natężenia czynników szkodliwych w środowisku pracy muszą być badane i oceniane pod kątem powodowanych dla pracowników zagrożeń. W warunkach zmiennych parametrów środowiska pracy wykrywanie potencjalnych zagrożeń i szybkie podejmowanie działań zmierzających do ograniczenia narażenia pracowników jest możliwe na podstawie ciągłego monitoringu parametrów środowiska pracy. Do tego celu mogą być wykorzystanie bezprzewodowe sieci sensorowe. W artykule omówiono strukturę i oraz główne zagadnienia opracowywanej w CIOP-PIB sieci sensorowej do monitorowania środowiska pracy i ostrzegania pracowników o zagrożeniach. Przedstawiono zastosowaną metodę lokalizacji ostrzeganego pracownika w obrębie sieci sensorowej, a także wyniki badań mocy sygnału radiowego, na bazie których funkcjonuje ta metoda.
EN
Concentrations and intensities of harmful factors in the work environment must be tested and assessed for hazards caused to employees. In conditions of changing parameters of the working environment, detection of potential threats and quick action to reduce employee exposure is possible based on the continuous monitoring of working environment parameters. Wireless sensor networks can be used for this purpose. The article discusses the structure and main issues of the sensor network being developed at CIOP-PIB to monitor the work environment and warn employees about hazards. The method used to locate the warned employee with in the sensor network was presented, as well as the results of radio signal strength measurements, on which this method works.
20
EN
We present a software platform for designing and testing wireless networks of sensors and actuators (WSNs). The platform consists of three components: an operating system for small-footprint microcontrollers (dubbed PicOS), a software development kit (SDK) amounting to a C-based, event-oriented (reactive) programming language, and a virtual execution platform (VUE2 ) capable of emulating complete deployment environments for WSNs and thus facilitating their rapid development.1 Its most recent incarnation introduced in the present paper is a component of the WSN lab being currently set up at Vistula in collaboration with Olsonet Communications Corporation. 2 We highlight the platform’s most interesting features within the context of a production WSN installed at independent-living facilities.
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