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  • Open Access

    ARTICLE

    Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

    Mohammad Riyaz Belgaum1, Fuead Ali1, Zainab Alansari2, Shahrulniza Musa1,*, Muhammad Mansoor Alam1,3, M. S. Mazliham4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 251-266, 2022, DOI:10.32604/cmc.2022.018211 - 07 September 2021

    Abstract Software-defined networking (SDN) plays a critical role in transforming networking from traditional to intelligent networking. The increasing demand for services from cloud users has increased the load on the network. An efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service (QoS). The multiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best algorithms. Moreover, the requests need to be transferred to reliable network elements. To… More >

  • Open Access

    ARTICLE

    Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

    Farhan Aadil1, Bilal Mehmood1, Najam Ul Hasan2, Sangsoon Lim3,*, Sadia Ejaz1, Noor Zaman4

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2499-2513, 2021, DOI:10.32604/cmc.2021.014647 - 13 April 2021

    Abstract A wireless body area network (WBAN) consists of tiny health-monitoring sensors implanted in or placed on the human body. These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things (IoT) systems. WBANs are connected to medical servers that monitor patients’ health. This type of network can protect critical patients’ lives due to the ability to monitor patients’ health continuously and remotely. The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely. However, during patient movement, the WBAN patient nodes… More >

  • Open Access

    ARTICLE

    Reconstruction and Optimization of Complex Network Community Structure under Deep Learning and Quantum Ant Colony Optimization Algorithm

    Peng Mei1, Gangyi Ding1, Qiankun Jin1, Fuquan Zhang2,*, Yeh-Cheng Chen3

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 159-171, 2021, DOI:10.32604/iasc.2021.012813 - 07 January 2021

    Abstract Community structure is a key component in complex network systems. This paper aims to improve the effectiveness of community detection and community discovery in complex network systems by providing directions for the reconstruction and optimization of community structures to expand the application of intelligent optimization algorithms in community structures. First, deep learning algorithms and ant colony algorithms are used to elaborate the community detection and community discovery in complex networks. Next, we introduce the technology of transfer learning and propose an algorithm of deep self-encoder modeling based on transfer learning (DSEM-TL). The DSEM-TL algorithm’s indicators… More >

  • Open Access

    ARTICLE

    IWD-Miner: A Novel Metaheuristic Algorithm for Medical Data Classification

    Sarab AlMuhaideb*, Reem BinGhannam, Nourah Alhelal, Shatha Alduheshi, Fatimah Alkhamees, Raghad Alsuhaibani

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1329-1346, 2021, DOI:10.32604/cmc.2020.013576 - 26 November 2020

    Abstract Medical data classification (MDC) refers to the application of classification methods on medical datasets. This work focuses on applying a classification task to medical datasets related to specific diseases in order to predict the associated diagnosis or prognosis. To gain experts’ trust, the prediction and the reasoning behind it are equally important. Accordingly, we confine our research to learn rule-based models because they are transparent and comprehensible. One approach to MDC involves the use of metaheuristic (MH) algorithms. Here we report on the development and testing of a novel MH algorithm: IWD-Miner. This algorithm can… More >

  • Open Access

    ARTICLE

    Personalized Nutrition Recommendation for Diabetic Patients Using Optimization Techniques

    Bhavithra Janakiraman1,*, Saradha Arumugam2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 269-280, 2020, DOI:10.31209/2019.100000150

    Abstract Personalization in recommendation system has been emerging as the most predominant area in service computing. Collaborative filtering and content based approaches are two major techniques applied for recommendation. However, to improve the accuracy and enhance user satisfaction, optimization techniques such as Ant Colony and Particle Swarm Optimization were analyzed in this paper. For theoretical analysis, this paper investigates web page recommender system. For experimentation, Diabetic patient’s health records were investigated and recommendation algorithms are applied to suggest appropriate nutrition for improving their health. Experiment result shows that Particle Swarm Optimization outperforms other traditional methods with More >

  • Open Access

    ARTICLE

    Hybrid Soft Computing Technique Based Trust Evaluation Protocol for Wireless Sensor Networks

    Supreet Kaur*, Vijay Kumar Joshi

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 217-226, 2020, DOI:10.31209/2018.100000064

    Abstract Wireless sensor networks (WSNs) are susceptible to safety threats due to cumulative dependence upon transmission, computing, and control mechanisms. Therefore, securing the end-to-end communication becomes a major area of research in WSNs. A majority of existing protocols are based upon signature and recommended-based trust evaluation techniques only. However, these techniques are vulnerable to wormhole attacks that happen due to lesser synchronization between the sensor nodes. Therefore, to handle this problem, a novel hybrid crossover-based ant colony optimization-based routing protocol is proposed. An integrated modified signature and recommendationbased trust evaluation protocol for WSNs is presented. Extensive More >

  • Open Access

    ARTICLE

    Discrete Wavelet Transmission and Modified PSO with ACO Based Feed Forward Neural Network Model for Brain Tumour Detection

    Machiraju Jayalakshmi1, *, S. Nagaraja Rao2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1081-1096, 2020, DOI:10.32604/cmc.2020.011710 - 20 August 2020

    Abstract In recent years, the development in the field of computer-aided diagnosis (CAD) has increased rapidly. Many traditional machine learning algorithms have been proposed for identifying the pathological brain using magnetic resonance images. The existing algorithms have drawbacks with respect to their accuracy, efficiency, and limited learning processes. To address these issues, we propose a pathological brain tumour detection method that utilizes the Weiner filter to improve the image contrast, 2D- discrete wavelet transformation (2D-DWT) to extract the features, probabilistic principal component analysis (PPCA) and linear discriminant analysis (LDA) to normalize and reduce the features, and More >

  • Open Access

    ARTICLE

    Ant Colony Optimization for Multi-Objective Multicast Routing

    Ahmed Y. Hamed1, Monagi H. Alkinani2, M. R. Hassan3, *

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1159-1173, 2020, DOI:10.32604/cmc.2020.09176 - 30 April 2020

    Abstract In the distributed networks, many applications send information from a source node to multiple destination nodes. To support these applications requirements, the paper presents a multi-objective algorithm based on ant colonies to construct a multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes total weight (cost, delay and hop) of the multicast tree. Experimental results prove the proposed algorithm outperforms a recently published Multi-objective Multicast Algorithm specially designed for solving the multicast routing problem. Also, it is able to find a better solution with fast convergence speed and high reliability. More >

  • Open Access

    ARTICLE

    Feature Selection and Representation of Evolutionary Algorithm on Keystroke Dynamics

    Purvashi Baynath, Sunjiv Soyjaudah, Maleika Heenaye-Mamode Khan

    Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 651-661, 2019, DOI:10.31209/2018.100000060

    Abstract The goal of this paper is (i) adopt fusion of features (ii) determine the best method of feature selection technique among ant Colony optimisation, artificial bee colony optimisation and genetic algorithm. The experimental results reported that ant colony Optimisation is a promising techniques as feature selection on Keystroke Dynamics as it outperforms in terms of recognition rate for our inbuilt database where the distance between the keys has been considered for the password derivation with recognition rate 97.85%. Finally the results have shown that a small improvement is obtained by fused features, which suggest that More >

  • Open Access

    ARTICLE

    CPAC: Energy-Efficient Algorithm for IoT Sensor Networks Based on Enhanced Hybrid Intelligent Swarm

    Qi Wang1,*, Wei Liu1, Hualong Yu1, Shang Zheng1, Shang Gao1, Fabrizio Granelli2

    CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.1, pp. 83-103, 2019, DOI:10.32604/cmes.2019.06897

    Abstract The wireless sensor network (WSN) is widely employed in the application scenarios of the Internet of Things (IoT) in recent years. Extending the lifetime of the entire system had become a significant challenge due to the energy-constrained fundamental limits of sensor nodes on the perceptual layer of IoT. The clustering routing structures are currently the most popular solution, which can effectively reduce the energy consumption of the entire network and improve its reliability. This paper introduces an enhanced hybrid intelligential algorithm based on particle swarm optimization (PSO) and ant colony optimization (ACO) method. The enhanced More >

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