Search Results - (( iot application clustering algorithm ) OR ( based application colony algorithm ))*

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    Authentication-chains: blockchain-inspired lightweight authentication protocol for IoT networks by Al Ahmed, Mahmoud Tayseer, Hashim, Fazirulhisyam, Hashim, Shaiful Jahari, Abdullah, Azizol

    Published 2023
    “…Internet of Things networks (IoT) are becoming very important in industrial, medical, and commercial applications. …”
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    Article
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    Blockchain based security framework for device authentication and data communication in decentralized IoT network by Alahmed, Mahmoud Tayseer

    Published 2023
    “…In light of the aforementioned issues, this thesis presents a lightweight, scalable, and secure authentication framework for IoT networks based on blockchain technology. First, this thesis proposes a clustering algorithm for IoT devices based on the device energy residues, the device location relative to other devices in the network, and the device computational ability. …”
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    Thesis
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    A Review on Attack Graph Analysis for IoT Vulnerability Assessment: Challenges, Open Issues, and Future Directions by Almazrouei O.S.M.B.H., Magalingam P., Hasan M.K., Shanmugam M.

    Published 2024
    “…In this review, core modeling techniques for IoT vulnerability assessment are highlighted, such as Markov Decision Processes (MDP), Feature Pyramid Networks (FPN), K-means clustering, and logistic regression models, along with other techniques involving genetic algorithms like fast-forward (FF), contingent fast-forwards (CFF), advanced reinforcement-learning algorithms, and HARMs models. …”
    Review
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    Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs by Azamuddin, Ab Rahman, Hamim, Sakib Iqram

    Published 2025
    “…This study introduces an enhanced energy aware clustering approach that combines an improved K-Means algorithm with an adaptive distance threshold to optimize relay node selection and cluster formation. …”
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    Article
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    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

    Published 2023
    “…The AGMB algorithm is built upon three algorithms: 1) Grid-Multi-Buffer Stream Clustering (GMBSC), 2) Cautious Grid-Multi-Buffer Stream Clustering (C-GMBSC) and 3) Adaptive-Grid-Multi-Buffer Stream Clustering (A-GMBSC). …”
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    Thesis
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    Analysis of Chinese patents associated with incremental clustering algorithms: A review / Archana Chaudhari by Chaudhari, Archana, Mulay, Preeti, Kumar Tiwari, Amit

    Published 2022
    “…To achieve learning from such dynamic data sources, incremental clustering algorithms are used mandatorily. This mandate has given rise to increased patents related to incremental clustering concept, which is primarily a significant part of Machine Learning field. …”
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    Lightweight ontology architecture for QoS aware service discovery and semantic CoAP data management in heterogeneous IoT environment by Sukhavasi, Suman, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

    Published 2026
    “…The architecture employs Modified-Ordered Points to Identify the Clustering Structure (M-OPTICS) to cluster and eliminate redundant IoT data. …”
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    Article
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    A trust aware secure ant colony optimization based routing algorithm for Internet of Things by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A., Hassan Abdalla Hashim, Aisha

    Published 2023
    “…The adoption of bio-inspired approaches contributes to discovering the optimal path for IoT routing by modeling the cognitive behavior of insect colonies to attain security cost-effectively. For wireless sensor network (WSN) integrated dynamic IoT networks, this paper presents a trust-aware secure Ant colony optimization (ACO)-based routing algorithm to provide security while searching for an energy-efficient optimal routing path. …”
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    Proceeding Paper
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    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

    Published 2023
    “…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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    Thesis