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  • Open Access

    ARTICLE

    A Bioinspired Method for Optimal Task Scheduling in Fog-Cloud Environment

    Ferzat Anka1, Ghanshyam G. Tejani2,3,*, Sunil Kumar Sharma4, Mohammed Baljon5

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2691-2724, 2025, DOI:10.32604/cmes.2025.061522 - 03 March 2025

    Abstract Due to the intense data flow in expanding Internet of Things (IoT) applications, a heavy processing cost and workload on the fog-cloud side become inevitable. One of the most critical challenges is optimal task scheduling. Since this is an NP-hard problem type, a metaheuristic approach can be a good option. This study introduces a novel enhancement to the Artificial Rabbits Optimization (ARO) algorithm by integrating Chaotic maps and Levy flight strategies (CLARO). This dual approach addresses the limitations of standard ARO in terms of population diversity and convergence speed. It is designed for task scheduling… More >

  • Open Access

    ARTICLE

    An Improved Chaotic Quantum Multi-Objective Harris Hawks Optimization Algorithm for Emergency Centers Site Selection Decision Problem

    Yuting Zhu1,*, Wenyu Zhang1,2, Hainan Wang1, Junjie Hou1, Haining Wang1, Meng Wang1

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2177-2198, 2025, DOI:10.32604/cmc.2024.057441 - 17 February 2025

    Abstract Addressing the complex issue of emergency resource distribution center site selection in uncertain environments, this study was conducted to comprehensively consider factors such as uncertainty parameters and the urgency of demand at disaster-affected sites. Firstly, urgency cost, economic cost, and transportation distance cost were identified as key objectives. The study applied fuzzy theory integration to construct a triangular fuzzy multi-objective site selection decision model. Next, the defuzzification theory transformed the fuzzy decision model into a precise one. Subsequently, an improved Chaotic Quantum Multi-Objective Harris Hawks Optimization (CQ-MOHHO) algorithm was proposed to solve the model. The… More >

  • Open Access

    ARTICLE

    Innovative Lightweight Encryption Schemes Leveraging Chaotic Systems for Secure Data Transmission

    Haider H. Al-Mahmood1,*, Saad N. Alsaad2

    Intelligent Automation & Soft Computing, Vol.40, pp. 53-74, 2025, DOI:10.32604/iasc.2024.059691 - 10 January 2025

    Abstract In secure communications, lightweight encryption has become crucial, particularly for resource-constrained applications such as embedded devices, wireless sensor networks, and the Internet of Things (IoT). As these systems proliferate, cryptographic approaches that provide robust security while minimizing computing overhead, energy consumption, and memory usage are becoming increasingly essential. This study examines lightweight encryption techniques utilizing chaotic maps to ensure secure data transmission. Two algorithms are proposed, both employing the Logistic map; the first approach utilizes two logistic chaotic maps, while the second algorithm employs a single logistic chaotic map. Algorithm 1, including a two-stage mechanism… More >

  • Open Access

    ARTICLE

    Hybrid Metaheuristic Lion and Firefly Optimization Algorithm with Chaotic Map for Substitution S-Box Design

    Arkan Kh Shakr Sabonchi*

    Journal of Information Hiding and Privacy Protection, Vol.6, pp. 21-45, 2024, DOI:10.32604/jihpp.2024.058954 - 31 December 2024

    Abstract Substitution boxes (S-boxes) are key components of symmetrical cryptosystems, acting as nonlinear substitution functions that hide the relationship between the encrypted text and input key. This confusion mechanism is vital for cryptographic security because it prevents attackers from intercepting the secret key by analyzing the encrypted text. Therefore, the S-box design is essential for the robustness of cryptographic systems, especially for the data encryption standard (DES) and advanced encryption standard (AES). This study focuses on the application of the firefly algorithm (FA) and metaheuristic lion optimization algorithm (LOA), thereby proposing a hybrid approach called the… More >

  • Open Access

    ARTICLE

    Secure Image Communication Using Galois Field, Hyper 3D Logistic Map, and B92 Quantum Protocol

    De Rosal Ignatius Moses Setiadi1,2, Nova Rijati2,*, Ahmad Rofiqul Muslikh3, Bonifacius Vicky Indriyono4, Aceng Sambas5,6

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4435-4463, 2024, DOI:10.32604/cmc.2024.058478 - 19 December 2024

    Abstract In this paper, we propose a novel secure image communication system that integrates quantum key distribution and hyperchaotic encryption techniques to ensure enhanced security for both key distribution and plaintext encryption. Specifically, we leverage the B92 Quantum Key Distribution (QKD) protocol to secure the distribution of encryption keys, which are further processed through Galois Field (GF(28)) operations for increased security. The encrypted plaintext is secured using a newly developed Hyper 3D Logistic Map (H3LM), a chaotic system that generates complex and unpredictable sequences, thereby ensuring strong confusion and diffusion in the encryption process. This hybrid approach More >

  • Open Access

    ARTICLE

    An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer Problem

    Feyza Altunbey Özbay1, Erdal Özbay2, Farhad Soleimanian Gharehchopogh3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1067-1110, 2024, DOI:10.32604/cmes.2024.054334 - 27 September 2024

    Abstract Artificial rabbits optimization (ARO) is a recently proposed biology-based optimization algorithm inspired by the detour foraging and random hiding behavior of rabbits in nature. However, for solving optimization problems, the ARO algorithm shows slow convergence speed and can fall into local minima. To overcome these drawbacks, this paper proposes chaotic opposition-based learning ARO (COARO), an improved version of the ARO algorithm that incorporates opposition-based learning (OBL) and chaotic local search (CLS) techniques. By adding OBL to ARO, the convergence speed of the algorithm increases and it explores the search space better. Chaotic maps in CLS… More > Graphic Abstract

    An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer Problem

  • Open Access

    ARTICLE

    BHJO: A Novel Hybrid Metaheuristic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfish Search Optimizers for Solving Engineering Design Problems

    Farouq Zitouni1,*, Saad Harous2, Abdulaziz S. Almazyad3, Ali Wagdy Mohamed4,5, Guojiang Xiong6, Fatima Zohra Khechiba1, Khadidja Kherchouche1

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 219-265, 2024, DOI:10.32604/cmes.2024.052001 - 20 August 2024

    Abstract Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization problems. This approach aims to leverage the strengths of multiple algorithms, enhancing solution quality, convergence speed, and robustness, thereby offering a more versatile and efficient means of solving intricate real-world optimization tasks. In this paper, we introduce a hybrid algorithm that amalgamates three distinct metaheuristics: the Beluga Whale Optimization (BWO), the Honey Badger Algorithm (HBA), and the Jellyfish Search (JS) optimizer. The proposed hybrid algorithm will be referred to as BHJO. Through this fusion, the BHJO algorithm aims to… More >

  • Open Access

    ARTICLE

    Multi-Level Image Segmentation Combining Chaotic Initialized Chimp Optimization Algorithm and Cauchy Mutation

    Shujing Li, Zhangfei Li, Wenhui Cheng, Chenyang Qi, Linguo Li*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2049-2063, 2024, DOI:10.32604/cmc.2024.051928 - 15 August 2024

    Abstract To enhance the diversity and distribution uniformity of initial population, as well as to avoid local extrema in the Chimp Optimization Algorithm (CHOA), this paper improves the CHOA based on chaos initialization and Cauchy mutation. First, Sin chaos is introduced to improve the random population initialization scheme of the CHOA, which not only guarantees the diversity of the population, but also enhances the distribution uniformity of the initial population. Next, Cauchy mutation is added to optimize the global search ability of the CHOA in the process of position (threshold) updating to avoid the CHOA falling More >

  • Open Access

    ARTICLE

    Fitness Sharing Chaotic Particle Swarm Optimization (FSCPSO): A Metaheuristic Approach for Allocating Dynamic Virtual Machine (VM) in Fog Computing Architecture

    Prasanna Kumar Kannughatta Ranganna1, Siddesh Gaddadevara Matt2, Chin-Ling Chen3,4,*, Ananda Babu Jayachandra5, Yong-Yuan Deng4,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2557-2578, 2024, DOI:10.32604/cmc.2024.051634 - 15 August 2024

    Abstract In recent decades, fog computing has played a vital role in executing parallel computational tasks, specifically, scientific workflow tasks. In cloud data centers, fog computing takes more time to run workflow applications. Therefore, it is essential to develop effective models for Virtual Machine (VM) allocation and task scheduling in fog computing environments. Effective task scheduling, VM migration, and allocation, altogether optimize the use of computational resources across different fog nodes. This process ensures that the tasks are executed with minimal energy consumption, which reduces the chances of resource bottlenecks. In this manuscript, the proposed framework… More >

  • Open Access

    ARTICLE

    A Multi-Strategy-Improved Northern Goshawk Optimization Algorithm for Global Optimization and Engineering Design

    Liang Zeng1,2, Mai Hu1, Chenning Zhang1, Quan Yuan1, Shanshan Wang1,2,*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1677-1709, 2024, DOI:10.32604/cmc.2024.049717 - 18 July 2024

    Abstract Optimization algorithms play a pivotal role in enhancing the performance and efficiency of systems across various scientific and engineering disciplines. To enhance the performance and alleviate the limitations of the Northern Goshawk Optimization (NGO) algorithm, particularly its tendency towards premature convergence and entrapment in local optima during function optimization processes, this study introduces an advanced Improved Northern Goshawk Optimization (INGO) algorithm. This algorithm incorporates a multifaceted enhancement strategy to boost operational efficiency. Initially, a tent chaotic map is employed in the initialization phase to generate a diverse initial population, providing high-quality feasible solutions. Subsequently, after… More >

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