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  • Open Access

    ARTICLE

    Fuzzy Firefly Based Intelligent Algorithm for Load Balancing in Mobile Cloud Computing

    Poonam*, Suman Sangwan

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1783-1799, 2023, DOI:10.32604/cmc.2023.031729

    Abstract This paper presents a novel fuzzy firefly-based intelligent algorithm for load balancing in mobile cloud computing while reducing makespan. The proposed technique implicitly acts intelligently by using inherent traits of fuzzy and firefly. It automatically adjusts its behavior or converges depending on the information gathered during the search process and objective function. It works for 3-tier architecture, including cloudlet and public cloud. As cloudlets have limited resources, fuzzy logic is used for cloudlet selection using capacity and waiting time as input. Fuzzy provides human-like decisions without using any mathematical model. Firefly is a powerful meta-heuristic optimization technique to balance diversification… More >

  • Open Access

    ARTICLE

    Shape and Size Optimization of Truss Structures under Frequency Constraints Based on Hybrid Sine Cosine Firefly Algorithm

    Ran Tao, Xiaomeng Yang, Huanlin Zhou*, Zeng Meng*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 405-428, 2023, DOI:10.32604/cmes.2022.020824

    Abstract Shape and size optimization with frequency constraints is a highly nonlinear problem with mixed design variables, non-convex search space, and multiple local optima. Therefore, a hybrid sine cosine firefly algorithm (HSCFA) is proposed to acquire more accurate solutions with less finite element analysis. The full attraction model of firefly algorithm (FA) is analyzed, and the factors that affect its computational efficiency and accuracy are revealed. A modified FA with simplified attraction model and adaptive parameter of sine cosine algorithm (SCA) is proposed to reduce the computational complexity and enhance the convergence rate. Then, the population is classified, and different populations… More >

  • Open Access

    ARTICLE

    Swarm Optimization and Machine Learning for Android Malware Detection

    K. Santosh Jhansi1,2,*, P. Ravi Kiran Varma2, Sujata Chakravarty3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6327-6345, 2022, DOI:10.32604/cmc.2022.030878

    Abstract Malware Security Intelligence constitutes the analysis of applications and their associated metadata for possible security threats. Application Programming Interfaces (API) calls contain valuable information that can help with malware identification. The malware analysis with reduced feature space helps for the efficient identification of malware. The goal of this research is to find the most informative features of API calls to improve the android malware detection accuracy. Three swarm optimization methods, viz., Ant Lion Optimization (ALO), Cuckoo Search Optimization (CSO), and Firefly Optimization (FO) are applied to API calls using auto-encoders for identification of most influential features. The nature-inspired wrapper-based algorithms… More >

  • Open Access

    ARTICLE

    Adaptive Window Based 3-D Feature Selection for Multispectral Image Classification Using Firefly Algorithm

    M. Rajakani1,*, R. J. Kavitha2, A. Ramachandran3

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 265-280, 2023, DOI:10.32604/csse.2023.024994

    Abstract Feature extraction is the most critical step in classification of multispectral image. The classification accuracy is mainly influenced by the feature sets that are selected to classify the image. In the past, handcrafted feature sets are used which are not adaptive for different image domains. To overcome this, an evolutionary learning method is developed to automatically learn the spatial-spectral features for classification. A modified Firefly Algorithm (FA) which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose. For extracting the most efficient features from the data set,… More >

  • Open Access

    ARTICLE

    Bio-inspired Hybrid Feature Selection Model for Intrusion Detection

    Adel Hamdan Mohammad1,*, Tariq Alwada’n2, Omar Almomani3, Sami Smadi3, Nidhal ElOmari4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 133-150, 2022, DOI:10.32604/cmc.2022.027475

    Abstract Intrusion detection is a serious and complex problem. Undoubtedly due to a large number of attacks around the world, the concept of intrusion detection has become very important. This research proposes a multilayer bio-inspired feature selection model for intrusion detection using an optimized genetic algorithm. Furthermore, the proposed multilayer model consists of two layers (layers 1 and 2). At layer 1, three algorithms are used for the feature selection. The algorithms used are Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Firefly Optimization Algorithm (FFA). At the end of layer 1, a priority value will be assigned for each… More >

  • Open Access

    ARTICLE

    Hybrid Renewable Energy System Using Cuckoo Firefly Optimization

    M. E. Shajini Sheeba1,*, P. Jagatheeswari2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1141-1156, 2022, DOI:10.32604/iasc.2022.024549

    Abstract With abundant and non-polluting benefits in nature, sources of renewable energy have reached vast concentrations. This paper first discusses the number of MPPT (Maximum Power Point Tracking) techniques utilized by wind and photovoltaic (PV) to create hybrid systems for generating wind-PV energy. This hybrid system complements each other day and night to enable continuous power output. Then, a new MPPT technique was proposed to extract maximum power using a newly developed hybrid optimization algorithm, namely the Cukoo Fire Fly method (CFF). The CFF algorithm is derived from the integration of the cuckoo search (CS) algorithm and the Firefly (FF) optimization… More >

  • Open Access

    ARTICLE

    Discrete Firefly Algorithm for Optimizing Topology Generation and Core Mapping of Network-on-Chip

    S. Parvathi*, S. Umamaheswari

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 15-32, 2022, DOI:10.32604/iasc.2022.025290

    Abstract Network-on-chip (NoC) proves to be the best alternative to replace the traditional bus-based interconnection in Multi-Processor System on a Chip (MPSoCs). Irregular NoC topologies are highly recommended and utilised in various applications as they are application specific. Optimized mapping of the cores in a NoC plays a major role in its performance. Firefly algorithm is a bio-inspired meta-heuristic approach. Discretized firefly algorithm is used in our proposed work. In this work, two optimization algorithms are proposed: Topology Generation using Discrete Firefly Algorithm (TGDFA) and Core Mapping using Discrete Firefly Algorithm (CMDFA) for multimedia benchmark applications, Video Object Plane Decoder (VOPD),… More >

  • Open Access

    ARTICLE

    Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System

    Harsh Goud1, Prakash Chandra Sharma2, Kashif Nisar3,7,*, Muhammad Reazul Haque4, Ag. Asri Ag. Ibrahim3, Narendra Singh Yadav2, Pankaj Swarnkar5, Manoj Gupta6, Laxmi Chand6

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3481-3492, 2022, DOI:10.32604/cmc.2022.019764

    Abstract Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response, less human interference, high dependability, improved hygiene, and reduced aging effects. That is why, in recent years, robotic aid has emerged as a blossoming solution to many challenges in the medical industry. In this manuscript, meta-heuristics (MH) algorithms, specifically the Firefly Algorithm (FF) and Genetic Algorithm (GA), are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd. The controller is used to control Mobile Robot System (MRS) at the required set… More >

  • Open Access

    ARTICLE

    A Chaotic Oppositional Whale Optimisation Algorithm with Firefly Search for Medical Diagnostics

    Milan Tair1, Nebojsa Bacanin1, Miodrag Zivkovic1, K. Venkatachalam2,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 959-982, 2022, DOI:10.32604/cmc.2022.024989

    Abstract There is a growing interest in the study development of artificial intelligence and machine learning, especially regarding the support vector machine pattern classification method. This study proposes an enhanced implementation of the well-known whale optimisation algorithm, which combines chaotic and opposition-based learning strategies, which is adopted for hyper-parameter optimisation and feature selection machine learning challenges. The whale optimisation algorithm is a relatively recent addition to the group of swarm intelligence algorithms commonly used for optimisation. The Proposed improved whale optimisation algorithm was first tested for standard unconstrained CEC2017 benchmark suite and it was later adapted for simultaneous feature selection and… More >

  • Open Access

    ARTICLE

    Hybrid Metaheuristics Web Service Composition Model for QoS Aware Services

    P. Rajeswari*, K. Jayashree

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 511-524, 2022, DOI:10.32604/csse.2022.020352

    Abstract Recent advancements in cloud computing (CC) technologies signified that several distinct web services are presently developed and exist at the cloud data centre. Currently, web service composition gains maximum attention among researchers due to its significance in real-time applications. Quality of Service (QoS) aware service composition concerned regarding the election of candidate services with the maximization of the whole QoS. But these models have failed to handle the uncertainties of QoS. The resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by end-users. On the other hand, trip planning is an… More >

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