23 research outputs found

    A Survey on Various Congestion Control Techniques in Wireless Sensor Networks

    Get PDF
    Wireless Sensor Networks (WSNs) are made up of small battery-powered sensors that can sense and monitor a variety of environmental conditions. These devices are self-contained and fault tolerant. The majority of WSNs are built to perform data collection tasks. These data are gathered and then sent to the sink node. Small packets are sent towards the sink node in such cases, and as a result, the areas near the sink node become congested, becoming the bottleneck of the entire network. In this paper, a survey of existing techniques or methods for detecting and eliminating congestions is conducted. Finally, a comparison in the form of a table based on various matrices is presented

    Hepatitis C cirrhosis: New perspectives for diagnosis and treatment

    No full text

    Review of Energy Aware Routing Algorithm in Wireless Sensor Network

    No full text
    Many energy efficient routing protocols have been proposed in sensor networks with different strategies. One of the efficient ways to is to group sensor in the neighbouring into clusters and send aggregate data by a nominated Cluster Head (CH). Though, such design discipline still cannot balance the energy consumption of the entire network. As such, in unfavourable cases, some nodes may be soon exhausted. Consequently, it is difficult to provide effective operation and seamless coverage in such a network. Therefore, designing energy saving routing algorithm is one of the most focused issues. In this review article, we studied energy aware routing algorithm for cluster based WSNs. The algorithm is based on a Brilliant strategy of cluster head (CH) selection, residual energy of the CHs and the intra cluster distance for cluster formation

    Energy Efficient Clustering Protocols in Wireless Sensor Network: A Survey

    No full text
    Wireless Sensor Network (WSN) consists of number of nodes which are randomly deployed in the network with some energy. All the nodes connect with each other to send and receive data. But this phenomenon can depleted their energy soon which results in decrease of network lifespan. To improve energy consumption clustering technique is used which can enhance stability, performance, lifespan and efficiency of the network. All the nodes in the network are well organized into clusters which consume less energy. In this article, survey on various routing protocols. From the survey, it does not conclude that any protocol perform well in all facet. But this end up with the future scope to overcome the issue of energy consumption

    Meltdown/Tantrum Detection System for Individuals with Autism Spectrum Disorder

    No full text
    The intensive and explosive behavioral problems associated with Autism Spectrum Disorder (ASD) are treated as ‘meltdown or tantrum,’ and it may lead to hyperactivity, impulsivity, aggression, self-injury, and irritability. The present work aims to propose and implement a noninvasive real-time deep learning based Meltdown/Tantrum Detection System (MTDS) for ASD individuals. The noninvasive physiological signals (such that heart rate, skin temperature, and galvanic skin response) were synthetically recorded with a specially designed hardware prototype. The recorded physiological signals were transmitted to an internet connected server where deep learning algorithms such as CNN, LSTM, and CNN-LSTM based Meltdown/Tantrum Detection System (MTDS) were implemented. The trained deep learning model was capable of detecting abnormal states of meltdown or tantrum through real-time received physiological signals. The proposed MTDS system was trained and tested with deep learning algorithms such as CNN, LSTM and hybrid CNN-LSTM, and it was found that hybrid CNN-LSTM was outperformed with an average training and testing accuracy of 96% with low MAE (0.10 for training and 0.04 for testing). Furthermore, 86% of the ASD caregivers favored the proposed MTDS system

    Performance Analysis of ERA Using Fuzzy Logic in Wireless Sensor Network

    No full text
    In Wireless Sensor Network (WSN), the main limitation is generally inimitable energy consumption during processing of the sensor nodes. Cluster head (CH) election is one of the main issues that can reduce the energy consumption. Therefore, discovering energy saving routing protocol is the focused area for research. In this paper, fuzzy-based energy aware routing protocol is presented, which enhances the stability and network lifetime of the network. Fuzzy logic ensures the well-organized selection of CH by taking four linguistic variables that are concentration, energy, centrality, and distance to base station (BS). The results show that the proposed protocol shows better results in requisites of stability and throughput of the network

    Performance Analysis of Deterministic Stable Election Protocol Using Fuzzy Logic in Wireless Sensor Network

    No full text
    In Wireless Sensor Network (WSN), the sensor containing motes (nodes) incorporate batteries that can lament at some extent. To upgrade the energy utilization, clustering is one of the prototypical approaches for split sensor motes into a number of clusters where one mote (also called as node) proceeds as a Cluster Head (CH). CH selection is one of the optimization techniques for enlarging stability and network lifespan. Deterministic Stable Election Protocol (DSEP) is an effectual clustering protocol that makes use of three kinds of nodes with dissimilar residual energy for CH election. Fuzzy Logic technology is used to expand energy level of DSEP protocol by using fuzzy inference system. This paper presents protocol DSEP using Fuzzy Logic (DSEP-FL) CH by taking into account four linguistic variables such as energy, concentration, centrality and distance to base station. Simulation results show that our proposed method gives more effective results in term of a lifespan of network and stability as compared to the performance of other clustering protocols
    corecore