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In disaster situations, the coordination of rescue missions is a difficult task. The person in charge makes decisions under pressure, which could lead to inappropriate instructions to rescuers and could cost many lives. The aim of DisVis 2.0 approach is to release pressure from those responsible by providing decision support using predictive human-centric disaster simulations for infrastructure-less...
In recent years, the research about energy waste and CO2 emission reduction has gained a strong momentum, also pushed by European and national funding initiatives. The main purpose of this large effort is to reduce the effects of greenhouse emission, climate change to head for a sustainable society. In this scenario, Information and Communication Technologies (ICT) play a key role. From one side,...
This article proposes a novel data gathering scheme for wireless sensor networks to reduce energy consumption for a prolonged network lifetime. Data gathering is modeled as random node sampling method, where fusion center collects data from arbitrarily deployed randomly selected nodes and takes the global decision. We evaluate performance of our method with metrics: energy consumption and error performance...
The instability of wireless links makes the choice of forwarding nodes have too many possibilities in opportunistic routing. In this paper, the Markov decision process (MDP) is used to model the whole packet forwarding process from the source node to the destination node, which facilitates making reasonable decisions when the sender selects the forwarding nodes. By solving a finite-state MDP problem,...
Wireless Sensor Networks (WSNs) security plays an intrinsic role to guarantee efficient data transmission, stable network topologies, and robust routing algorithms. In this paper, we propose a modified Stackelberg game of a previous work for high assurance of data trustworthiness in a Power Grid Network (PGN). The proposed approach is presented to mitigate a more severe attack scenario compared to...
With the arrival of big data era, data mining techniques have been widely used to build models for cyber security applications such as spam filtering, malware or virus detection, and intrusion detection. This project proposes a novel approach that uses randomness to improve robustness of data mining models used in cyber security applications against attacks that try to evade detection by adapting...
Data muling using UAVs/drones is currently emerging as an alternative to the traditional traffic engineering techniques used in wireless sensor networks, when wireless communication is not an option or the least cost-efficient solution. This paper revisits the issue of traffic engineering in Internet-of-Things (IoT) settings, to assess the relevance of using UAVs for the persistent collection of sensor...
Temporal drift of sensory data is a severe problem impacting the data quality of wireless sensor networks (WSNs). With the proliferation of large-scale and long-term WSNs, it is becoming more important to calibrate sensors when the ground truth is unavailable. This problem is called ”blind calibration”. In this paper, we propose a novel deep learning method named projection-recovery network (PRNet)...
Wireless sensor networks (WSNs) are usually deployed in insecure remote and open environments. Nodes could be attacked and compromised. The attacker can use compromised sensor nodes to disrupt communications or inject misleading sensor values. Misleading data can corrupt the entire decision making process, which depends upon WSN data. We propose a trust mechanism, which evaluates communication trust...
5G and Internet of things (IOT) develop rapidly, but the major applications of IOT-wireless sensor networks(WSNs) have numerous data, resulting in serious transmission load. In order to reduce the number of transmitted packets, this paper focuses on data aggregation for WSNs and proposes a novel event-based data aggregation mechanism using both principle component analysis(PCA) and support vector...
MapReduce function is a programming paradigm for processing input datasets in a parallel manner. In this paper, we have utilized this function for identifying and predicting health data collected from smart homes to help elderly people to live independently in their own home longer away from hospitals. Statistical techniques running in parallel multiple MapReduce functions are used. The proposed approach...
Reliability is an important research issue in wireless sensor networks(WSNs). Many literatures about how to improve network reliability in WSNs have been proposed, however the research on establishing evaluation models of reliability for WSNs is yet insufficient. In this paper, a model to evaluate the reliability of wireless sensor networks (WSNs) is proposed. This network state based model can effectively...
In the wireless sensor actuator network (WSAN), in order to make the sensor nodes (S) and the actuator nodes (A) work together more efficiently and obtain more accurate assignment information of actuators, a novel data fusion model of actuators assignment were constructed. In this paper, the weights and thresholds of BP neural network (BPNN) were optimized by genetic algorithm (GA), and the GA-BPNN...
In conventional wireless sensor networks (hereinafter referred to as WSNs), the single sink node model has been employed to collect and store the measured data that can be accessed by external users of WSNs. However, the single sink model of WSNs can be the single point of failure for some usage. To counter this problem, we can employ multiple gateway-based WSNs. In addition, WSNs are susceptible...
Clustering is one of the most useful methods for data gathering in distributed wireless sensor networks (WSNs). In additions, sensors in such environment are energy constrained and generate the huge amount of data due to redundant data transmission and thus reducing lifetime of networks. Moreover, there is need to use efficient clustering techniques for collecting relevant data from nodes to eliminate...
Wireless Sensor Networks (WSNs) allow applications to interact with the physical world using nodes in an Internet of Things (IoT). Application level protocols such as the Constrained Application Protocol (CoAP) and data models such as IPSO Smart Objects and the Open Mobile Alliance Lightweight Specification (OMA LWM2M) have the potential to provide greater application interoperability and to ease...
This paper proposes an efficient decoupling model for information producer (IPD) (i.e., physical sensor) and information provider (IPV) toward a semantic sensor-cloud integration to improve Wireless Sensor Networks' (WSN) lifetime. In particular, while IPDs produce sensing information, their IPVs, which are designed as virtual sensors on sensor-cloud based on network function virtualization, are responsible...
Energy consumption in general is one of biggest challenges when it comes to wireless sensor networks (WSNs). Since the biggest amount of energy is used for communication, the most logical way to reduce the energy consumption is to reduce the number of packets transmitted between sensor and sink node. To address this issue, data reduction methods, which are predicting the measured values both at source...
This paper develops a mathematical model to determine the balance of energy input and data sensing and transmission in a wireless sensing node. Since the node acquires energy through harvesting from an intermittent source, and sensing is also carried out intermittently, the node is modelled with random arrivals of both energy and data. A buffer in the node stores data packets while energy is stored...
We consider the operation of an energy harvesting wireless device (sensor node) powered by a rechargeable battery, taking non-idealities into account. In particular, we consider sudden decrease and increase of the battery level (leakage and charge recovery consequently) due to the inner diffusion processes in the battery. These processes are affecting the stability of the device operation. In particular,...
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