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  • Open Access


    An Optimal Cluster Head and Gateway Node Selection with Fault Tolerance

    P. Rahul*, B. Kaarthick

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1595-1609, 2023, DOI:10.32604/iasc.2023.025762

    Abstract In Mobile Ad Hoc Networks (MANET), Quality of Service (QoS) is an important factor that must be analysed for the showing the better performance. The Node Quality-based Clustering Algorithm using Fuzzy-Fruit Fly Optimization for Cluster Head and Gateway Selection (NQCAFFFOCHGS) has the best network performance because it uses the Improved Weighted Clustering Algorithm (IWCA) to cluster the network and the FFO algorithm, which uses fuzzy-based network metrics to select the best CH and entryway. However, the major drawback of the fuzzy system was to appropriately select the membership functions. Also, the network metrics related to… More >

  • Open Access


    CNR: A Cluster-Based Solution for Connectivity Restoration for Mobile WSNs

    Mahmood ul Hassan1,*, Amin Al-Awady1, Khalid Mahmood2, Shahzad Ali3, Ibrahim Algamdi1, Muhammad Kashif Saeed4, Safdar Zaman5

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3413-3427, 2021, DOI:10.32604/cmc.2021.018544

    Abstract Wireless Sensor Networks (WSNs) are an integral part of the Internet of Things (IoT) and are widely used in a plethora of applications. Typically, sensor networks operate in harsh environments where human intervention is often restricted, which makes battery replacement for sensor nodes impractical. Node failure due to battery drainage or harsh environmental conditions poses serious challenges to the connectivity of the network. Without a connectivity restoration mechanism, node failures ultimately lead to a network partition, which affects the basic function of the sensor network. Therefore, the research community actively concentrates on addressing and solving… More >

  • Open Access


    ANN Based Novel Approach to Detect Node Failure in Wireless Sensor Network

    Sundresan Perumal1, Mujahid Tabassum1, Ganthan Narayana2, Suresh Ponnan3,*, Chinmay Chakraborty4, Saju Mohanan5, Zeeshan Basit5, Mohammad Tabrez Quasim6

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1447-1462, 2021, DOI:10.32604/cmc.2021.014854

    Abstract A wireless sensor network (WSN) consists of several tiny sensor nodes to monitor, collect, and transmit the physical information from an environment through the wireless channel. The node failure is considered as one of the main issues in the WSN which creates higher packet drop, delay, and energy consumption during the communication. Although the node failure occurred mostly due to persistent energy exhaustion during transmission of data packets. In this paper, Artificial Neural Network (ANN) based Node Failure Detection (NFD) is developed with cognitive radio for detecting the location of the node failure. The ad hocMore >

  • Open Access


    An Efficient Connectivity Restoration Technique (ECRT) for Wireless Sensor Network

    Mahmood ul Hassan1,*, Shahzad Ali2, Khalid Mahmood3, Muhammad Kashif Saeed4, Amin Al-Awady1, Kamran Javed5, Ansar Munir Shah6

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1003-1019, 2021, DOI:10.32604/cmc.2021.018264

    Abstract Node failure in Wireless Sensor Networks (WSNs) is a fundamental problem because WSNs operate in hostile environments. The failure of nodes leads to network partitioning that may compromise the basic operation of the sensor network. To deal with such situations, a rapid recovery mechanism is required for restoring inter-node connectivity. Due to the immense importance and need for a recovery mechanism, several different approaches are proposed in the literature. However, the proposed approaches have shortcomings because they do not focus on energy-efficient operation and coverage-aware mechanisms while performing connectivity restoration. Moreover, most of these approaches… More >

  • Open Access


    FP-STE: A Novel Node Failure Prediction Method Based on Spatio-Temporal Feature Extraction in Data Centers

    Yang Yang1,*, Jing Dong1, Chao Fang2, Ping Xie3, Na An3

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1015-1031, 2020, DOI:10.32604/cmes.2020.09404

    Abstract The development of cloud computing and virtualization technology has brought great challenges to the reliability of data center services. Data centers typically contain a large number of compute and storage nodes which may fail and affect the quality of service. Failure prediction is an important means of ensuring service availability. Predicting node failure in cloud-based data centers is challenging because the failure symptoms reflected have complex characteristics, and the distribution imbalance between the failure sample and the normal sample is widespread, resulting in inaccurate failure prediction. Targeting these challenges, this paper proposes a novel failure… More >

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