Journal Articles

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884

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    A Hybrid Trust Management Scheme for Wireless Sensor Networks
    (Springer New York LLC barbara.b.bertram@gsk.com, 2017) Karthik, N.; Ananthanarayana, V.S.
    Wireless sensor network (WSN) consists of wireless small sensor nodes deployed in the terrain for continuous observation of physical or environmental conditions. The data collected from the WSN is used for making decisions. The condition for making critical decision is to assure the trustworthiness of the data generated from sensor nodes. However, the approaches for scoring the sensed data alone is not enough in WSN since there is an interdependency between node and data item. If the overall trust score of the network is based on one trust component, then the network might be misguided. In this work, we propose the hybrid approach to address the issue by assigning the trust score to data items and sensor nodes based on data quality and communication trust respectively. The proposed hybrid trust management scheme (HTMS) detects the data fault with the help of temporal and spatial correlations. The correlation metric and provenance data are used to score the sensed data. The data trust score is utilized for making decision. The communication trust and provenance data are used to evaluate the trust score of intermediate nodes and source node. If the data item is reliable enough to make critical decisions, a reward is given by means of adding trust score to the intermediate nodes and source node. A punishment is given by reducing the trust score of the source and intermediate nodes, if the data item is not reliable enough to make critical decisions. Result shows that the proposed HTMS detects the malicious, faulty, selfish node and untrustworthy data. © 2017, Springer Science+Business Media, LLC.
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    Context Aware Trust Management Scheme for Pervasive Healthcare
    (Springer New York LLC barbara.b.bertram@gsk.com, 2019) Karthik, N.; Ananthanarayana, V.S.
    Medical sensor nodes are used in pervasive healthcare applications like remote patient monitoring, elderly care to collect patients vital signs for identifying medical emergency. These resource restricted sensor nodes are prone to various malicious attacks, data faults and data losses. Presence of faulty data, data loss in collected patient data may lead to incorrect analysis of patient condition, which decreases the reliability of pervasive healthcare system. The aim of this work is to alert the caregiver and raise the alarm only when the patient enters into medical emergency situation. The proposed scheme also reduces the false alarms and alerts caused by data fault and misbehaving sensor nodes. To achieve this, we introduce a context aware trust management scheme for data fault detection, data reconstruction and event detection in pervasive healthcare systems. It employs heuristic functions, data correlation and contextual information based algorithms to identify the data faults and events. It also reconstructs the data faults and data loss for identifying patient condition. Performance of this approach is evaluated with the help of real data samples collected by medical sensor network prototype of remote patient monitoring application. The experimental results show that the proposed trust scheme outperforms state-of-the-art techniques and achieves good detection accuracy in data fault detection and event detection. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
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    Trust Based Data Gathering in Wireless Sensor Network
    (Springer New York LLC barbara.b.bertram@gsk.com, 2019) Karthik, N.; Ananthanarayana, V.S.
    Wireless sensor nodes have been successfully employed in various pervasive applications. In all pervasive applications, a gathering of sensor data from the environment is the main operation held in a sensor network, where sink node or base station gathers all generated data to do data analysis and decision making. The data generated by the sensor node in the pervasive environment should be transmitted to the sink node for data analysis and decision making. We strongly conceive that each process from perceiving the environment to decision making, demands trust based process to ease and ensure the trustworthy data exchange among trustworthy nodes such as trust-based data collection, trust-based data aggregation, trust-based data reconstruction and trust-based data analysis for decision making. In this work, we propose a Trust-based Data Gathering which focus on trust-based data collection, data aggregation, and data reconstruction to show that the absence of trust in a sensor-driven pervasive environment could affect the normal functionality of an application. Experimental results show that the proposed method achieves better performance in detecting data faults, malicious nodes and demonstrates that the absence of trust based process in data collection, data aggregation, and data reconstruction in harsh environment consumes more energy and delay for handling untrustworthy data, untrustworthy node and affects the normal functionality of the application. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
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    IoT energy efficiency routing protocol using FHO-based clustering and improved CSO model-based routing in MANET
    (John Wiley and Sons Ltd, 2024) Sanshi, S.; Karthik, N.; Vatambeti, R.
    Many protocols, services, and electrical devices with built-in sensors have been developed in response to the rapid expansion of the Internet of Things. Mobile ad hoc networks (MANETs) consist of a collection of autonomous mobile nodes that can form an ad hoc network in the absence of any pre-existing infrastructure. System performance may suffer due to the changeable topology of MANETs. Since most mobile hosts operate on limited battery power, energy consumption poses the biggest challenge for MANETs. Both network lifetime and throughput improve when energy usage is reduced. However, existing approaches perform poorly in terms of energy efficiency. Scalability becomes a significant issue in large-scale networks as they grow, leading to overhead associated with routing updates and maintenance that can become unmanageable. This article employs a MANET routing protocol combined with an energy conservation strategy. The clustering hierarchy is used in MANETs to maximize the network's lifespan, considering its limited energy resources. In the MANET communication process, the cluster head (CH) is selected using Fire Hawk Optimization (FHO). When choosing nodes to act as a cluster for an extended period, CH election factors in connectivity, mobility, and remaining energy. This process is achieved using an optimized version of the Ad hoc On-Demand Distance Vector (AODV) routing protocol, utilizing Improved Chicken Swarm Optimization (ICSO). In comparison to existing protocols and optimization techniques, the proposed method offers an extended network lifespan ranging from 90 to 160 h and reduced energy consumption of 80 to 110 J, as indicated by the implementation results. © 2024 John Wiley & Sons Ltd.