Yazar "Nguyen, Tu N." seçeneğine göre listele

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    3D Localization and Error Minimization in Underwater Sensor Networks
    (Assoc Computing Machinery, 2022) Sah, Dinesh Kumar; Nguyen, Tu N.; Kandulna, Manjusha; Cengiz, Korhan; Amgoth, Tarachand
    Wireless sensor networks (WSNs) consist of nodes distributed in the region of interest (ROI) that forward collected data to the sink. The node's location plays a vital role in data forwarding to enhance network efficiency by reducing the packet drop rate and energy consumption. WSN scenarios, such as tracking, smart cities, and agriculture applications, require location details to accomplish the objective. Assuming a 3D application space, a combination of received signal strength (RSS) and time of arrival (TOA) can be helpful for reliable range estimation of nodes. Notably, the anchor node can minimize localization error for non-line-of-sight (NLOS) signals. We proposed an error minimization protocol for localization of the sensor node, assuming that the anchor node's location is known prior and can limit the receiving signal in LOS, single, or twice reflection. We start to exploit the sensor node's geometrical relationship and the anchor node for LOS and NLOS signals and address misclassification. We started initially from the erroneous node position, bound its volume in 3D space, and reduced volume with each iteration following the constraint. Our simulation result outperforms the traditional methods on many occasions, such as boundary volume and computational complexity.
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    An accurate and exact clustering algorithm for next generation sequencing metagenomic sequences
    (Wiley, 2021) Bhat, Ashaq Hussain; Nguyen, Tu N.; Cengiz, Korhan; Prabhu, Puniethaa
    Clustering algorithms are the essential tools in the target metagenomics, used to perform the taxonomic profiling of microbial communities. In the present study, an algorithmic tool called hash-based exact alignment (HBEA) clustering algorithm is presented, which uses exact pairwise global alignment algorithm to improve the cluster quality and creates a hash table for extraction of cluster representatives. The algorithm is de novo based and uses the general de facto 97% sequence similarity score to cluster the sequences. Our experimental investigation on various types of datasets with distinct parameters and attributes showed that HBEA produces better operational taxonomic unit (OTU) clusters and computational complexity than other algorithms.
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    Fine-tuned support vector regression model for stock predictions
    (Springer London Ltd, 2023) Dash, Ranjan Kumar; Nguyen, Tu N.; Cengiz, Korhan; Sharma, Aditi
    In this paper, a new machine learning (ML) technique is proposed that uses the fine-tuned version of support vector regression for stock forecasting of time series data. Grid search technique is applied over training dataset to select the best kernel function and to optimize its parameters. The optimized parameters are validated through validation dataset. Thus, the tuning of this parameters to their optimized value not only increases model's overall accuracy but also requires less time and memory. Further, this also minimizes the model from being data overfitted. The proposed method is used to analysis different performance parameters of stock market like up-to-daily and up-to-monthly return, cumulative monthly return, its volatility nature and the risk associated with it. Eight different large-sized datasets are chosen from different domain, and stock is predicted for each case by using the proposed method. A comparison is carried out among the proposed method and some similar methods of same interest in terms of computed root mean square error and the mean absolute percentage error. The comparison reveals the proposed method to be more accurate in predicting the stocks for the chosen datasets. Further, the proposed method requires much less time than its counterpart methods.
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    Global cryptocurrency trend prediction using social media
    (Elsevier Sci Ltd, 2021) Poongodi, M.; Nguyen, Tu N.; Hamdi, Mounir; Cengiz, Korhan
    This paper aims to investigate the global crypto-currency price movement trends with respect to the social media communication data. The idea is to analyze the topical trends in the online communities and social media platforms to understand and extract insights that could be used to predict the price fluctuations in crypto-currencies. The hypothesis rests in finding the empirical evidence to exploit the relationship between price variations and social media activities. Such models and insights will help us better understand the crypto currency ecosystems in context of social media behavior which can be used for real-time trading systems.
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    Hybrid Cache Management in IoT-Based Named Data Networking
    (IEEE-Inst Electrical Electronics Engineers Inc, 2022) Naeem, Muhammad Ali; Nguyen, Tu N.; Ali, Rashid; Cengiz, Korhan; Meng, Yahui; Khurshaid, Tahir
    Internet of Things (IoT) and named data network (NDN) are innovative technologies to meet up the future Internet requirements. NDN is considered as an enabling approach to improving data dissemination in IoT scenarios. NDN delivers in-network caching, which is the most prominent feature to provide fast data dissemination as compared to Internet protocol (IP)-based communication. The proper integration of caching placement strategies and replacement policies is the most suitable approach to support IoT networks. It can improve multicast communication which minimizes the delay in responding to IoT-based environments. Besides, these approaches are playing a most significant role in increasing the overall performance of NDN-based IoT networks. To this end, in this article, the challenges of NDN-IoT caching are identified with the aim to develop a new hybrid strategy for efficient data delivery. The proposed strategy is comparatively and extensively studied with NDN-IoT caching strategies through an extensive simulation in terms of average latency, cache hit ratio, and average stretch ratio. From the simulation findings, it is observed that the proposed hybrid strategy outperformed to achieve a higher caching performance of NDN-based IoT scenarios.
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    Lattice-based cryptosystems for the security of resource-constrained IoT devices in post-quantum world: a survey
    (Springer, 2022) Seyhan, Kubra; Nguyen, Tu N.; Akleylek, Sedat; Cengiz, Korhan
    The concept of the Internet of Things (IoT) arises due to the change in the characteristics and numbers of smart devices. Communication of things makes it important to ensure security in this interactive architecture. One of the developments that are subject to change in IoT environments is post-quantum cryptography. This evolution, which includes the change of asymmetric cryptosystems, affects the security of IoT devices. In this paper, fundamental characteristics and layered architecture of IoT environments are examined. Basic security requirements and solution technologies for IoT architecture are remembered. Some important open problems in the literature for IoT device security are recalled. From these open problems, the post-quantum security of IoT devices with limited resources is focused. The main purpose of this paper is to improve the constrained resource classification and give a point of view for post-quantum IoT security. In this context, a sensitive classification is proposed by improving the limited resource classification of IETF. The cryptosystem efficiency definition is made for the analysis of resource-constrained device security. Using the proposed classification and efficiency definition, the usage of lattice-based cryptosystems in resource-constrained IoT device security is analyzed.
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    Lightweight batch authentication and privacy-preserving scheme for online education system
    (Pergamon-Elsevier Science Ltd, 2021) Subramani, Jegadeesan; Nguyen, Tu N.; Maria, Azees; Rajasekaran, Arun Sekar; Cengiz, Korhan
    Nowadays, the online education system (OES) attracts learners to improve their knowledge and skills through learning flexibility and efficient assessment procedures. The learner can learn the courses and obtain a degree in a comfortable place, no need to go to school or college. Physical verification in the traditional education system is replaced by a secure authentication process. Many authentication schemes are existing to provide authentication, but they are suffering from authentication burden, due to high computational cost. In this work, two batch authentication schemes are introduced to validate the multiple learners and batch of messages/materials simultaneously instead of authenticating one after another. It reduces the authentication burden during the learner registration and message/material distribution process. The security and performance analysis sections ensures that the proposed scheme provides the essential security features with less computational costs compared to that of existing competitive schemes.
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    Load-balance scheduling for intelligent sensors deployment in industrial internet of things
    (Springer, 2022) Sah, Dinesh Kumar; Nguyen, Tu N.; Cengiz, Korhan; Dumba, Braulio; Kumar, Vikas
    The Industrial Internet of Things uses intelligent sensors to collect the physical properties of objects placed on a large area. It provides innovative service and network functioning, such as time-bounded data delivery and efficient sensor sleep cycle management. Intelligent scheduling is crucial to assisting the situation. The periodic scheduling of radio transceivers of sensor nodes into sleep or active mode helps accomplish efficient energy consumption. Such an extensive scale network work on data collection on multihop fashion. Our proposal provides the algorithm to form the node's backbone, which task is to collect the data from sensors scatted in the area. Further, the heuristic algorithm is proposed to assist the backbone node in balancing the incoming traffic for scheduling. In Time Division Multiple Access (TDMA) driven Medium Access Control (MAC), the nodes are scheduled for data forwarding in the allotted time slot (owner node) in each time frame. Our proposed work is named aggressive scheduling medium access control (AS-MAC). If the owner node does not have data to forward, then the corresponding slot will be aggressively scheduled by other nodes. Therefore, that slot and all consecutive slots if the corresponding owner nodes do not use will go to the needy nodes. The proposed system model presents a unique instance of interference for successfully delivering control and data packets. Therefore, a probabilistic estimation has given for the packet delivery rate for the raised specific condition. Our proposal's distinctive feature is that the performance is better than Time Division Multiple Access for any given load. Finally, the packet delivery rate, packet drop, energy consumption, and time frame requirement for a different number of sensor node has been calculated and compared with the current state-of-the-art proposals.
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    Towards sustainable energy efficient routing for dynamic ad-hoc communications in smart cities
    (Elsevier Sci Ltd, 2022) Vijayalakshmi, P.; Nguyen, Tu N.; Dinakaran, J. Abraham; Cengiz, Korhan
    The minimal energy-efficiency in ad-hoc environment usually selects path with minimal energy path cost in multi hop communications. Choosing a path with minimal energy path cost does not guarantee in link stability and reliability of individual nodes in the network. A novel energy-efficient routing protocol named as Link Error Recovery Max-Min Path (LER-MMP) has been proposed. This protocol includes total energy spent on reliable transmission forl optimized paths in dynamic network. The link error rate that affects re-transmission with increased transmission error rate and therefore LER-MMP protocol selects an efficient path that has less number of long-distance hops for reliable network connectivity. The simulation result proves that LER-MMP can adapt reliable re-transmission with less link error rate and outperforms than existing protocols. The statistical result shows that LER-MMP protocol is efficient during link disconnections for concurrent communications in dynamic smart city environment.