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Search Results (14)
  • Open Access

    ARTICLE

    Adaptive Resource Allocation Algorithm for 5G Vehicular Cloud Communication

    Huanhuan Li1,2,*, Hongchang Wei2, Zheliang Chen2, Yue Xu3

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2199-2219, 2024, DOI:10.32604/cmc.2024.052155 - 15 August 2024

    Abstract The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges, such as low user utilization, unbalanced resource allocation, and extended adaptive allocation time. We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues. This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components. It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes. Furthermore, this study analyzes the single-hop and multi-hop modes in… More >

  • Open Access

    ARTICLE

    Distributed Stochastic Optimization with Compression for Non-Strongly Convex Objectives

    Xuanjie Li, Yuedong Xu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 459-481, 2024, DOI:10.32604/cmes.2023.043247 - 30 December 2023

    Abstract We are investigating the distributed optimization problem, where a network of nodes works together to minimize a global objective that is a finite sum of their stored local functions. Since nodes exchange optimization parameters through the wireless network, large-scale training models can create communication bottlenecks, resulting in slower training times. To address this issue, CHOCO-SGD was proposed, which allows compressing information with arbitrary precision without reducing the convergence rate for strongly convex objective functions. Nevertheless, most convex functions are not strongly convex (such as logistic regression or Lasso), which raises the question of whether this… More >

  • Open Access

    ARTICLE

    A Sensor Network Coverage Planning Based on Adjusted Single Candidate Optimizer

    Trong-The Nguyen1,2,3, Thi-Kien Dao1,2,3,*, Trinh-Dong Nguyen2,3

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3213-3234, 2023, DOI:10.32604/iasc.2023.041356 - 11 September 2023

    Abstract Wireless sensor networks (WSNs) are widely used for various practical applications due to their simplicity and versatility. The quality of service in WSNs is greatly influenced by the coverage, which directly affects the monitoring capacity of the target region. However, low WSN coverage and uneven distribution of nodes in random deployments pose significant challenges. This study proposes an optimal node planning strategy for network coverage based on an adjusted single candidate optimizer (ASCO) to address these issues. The single candidate optimizer (SCO) is a metaheuristic algorithm with stable implementation procedures. However, it has limitations in More >

  • Open Access

    ARTICLE

    Determination of AVR System PID Controller Parameters Using Improved Variants of Reptile Search Algorithm and a Novel Objective Function

    Baran Hekimoğlu*

    Energy Engineering, Vol.120, No.7, pp. 1515-1540, 2023, DOI:10.32604/ee.2023.029024 - 04 May 2023

    Abstract Two novel improved variants of reptile search algorithm (RSA), RSA with opposition-based learning (ORSA) and hybrid ORSA with pattern search (ORSAPS), are proposed to determine the proportional, integral, and derivative (PID) controller parameters of an automatic voltage regulator (AVR) system using a novel objective function with augmented flexibility. In the proposed algorithms, the opposition-based learning technique improves the global search abilities of the original RSA algorithm, while the hybridization with the pattern search (PS) algorithm improves the local search abilities. Both algorithms are compared with the original RSA algorithm and have shown to be highly… More > Graphic Abstract

    Determination of AVR System PID Controller Parameters Using Improved Variants of Reptile Search Algorithm and a Novel Objective Function

  • Open Access

    ARTICLE

    Sea Turtle Foraging Optimization-Based Controller Placement with Blockchain-Assisted Intrusion Detection in Software-Defined Networks

    Sultan Alkhliwi*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4735-4752, 2023, DOI:10.32604/cmc.2023.037141 - 29 April 2023

    Abstract Software-defined networking (SDN) algorithms are gaining increasing interest and are making networks flexible and agile. The basic idea of SDN is to move the control planes to more than one server’s named controllers and limit the data planes to numerous sending network components, enabling flexible and dynamic network management. A distinctive characteristic of SDN is that it can logically centralize the control plane by utilizing many physical controllers. The deployment of the controller—that is, the controller placement problem (CPP)—becomes a vital model challenge. Through the advancements of blockchain technology, data integrity between nodes can be… More >

  • Open Access

    ARTICLE

    Enhanced Water Quality Control Based on Predictive Optimization for Smart Fish Farming

    Azimbek Khudoyberdiev1, Mohammed Abdul Jaleel1, Israr Ullah2, DoHyeun Kim3,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5471-5499, 2023, DOI:10.32604/cmc.2023.036898 - 29 April 2023

    Abstract The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource limitations. Internet of Things (IoT) based Modern fish farming systems can significantly optimize seafood production by minimizing resource utilization and improving healthy fish production. This objective requires intensive monitoring, prediction, and control by optimizing leading factors that impact fish growth, including temperature, the potential of hydrogen (pH), water level, and feeding rate. This paper proposes the IoT based predictive optimization approach for efficient control and energy utilization in smart fish farming. The proposed fish farm control… More >

  • Open Access

    ARTICLE

    Deep Learning-Based FOPID Controller for Cascaded DC-DC Converters

    S. Hema1,*, Y. Sukhi2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1503-1519, 2023, DOI:10.32604/csse.2023.036577 - 09 February 2023

    Abstract Smart grids and their technologies transform the traditional electric grids to assure safe, secure, cost-effective, and reliable power transmission. Non-linear phenomena in power systems, such as voltage collapse and oscillatory phenomena, can be investigated by chaos theory. Recently, renewable energy resources, such as wind turbines, and solar photovoltaic (PV) arrays, have been widely used for electric power generation. The design of the controller for the direct Current (DC) converter in a PV system is performed based on the linearized model at an appropriate operating point. However, these operating points are ever-changing in a PV system,… More >

  • Open Access

    ARTICLE

    Honey Badger Algorithm Based Clustering with Routing Protocol for Wireless Sensor Networks

    K. Arutchelvan1, R. Sathiya Priya1,*, C. Bhuvaneswari2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3199-3212, 2023, DOI:10.32604/iasc.2023.029804 - 17 August 2022

    Abstract Wireless sensor network (WSN) includes a set of self-organizing and homogenous nodes employed for data collection and tracking applications. It comprises a massive set of nodes with restricted energy and processing abilities. Energy dissipation is a major concern involved in the design of WSN. Clustering and routing protocols are considered effective ways to reduce the quantity of energy dissipation using metaheuristic algorithms. In order to design an energy aware cluster-based route planning scheme, this study introduces a novel Honey Badger Based Clustering with African Vulture Optimization based Routing (HBAC-AVOR) protocol for WSN. The presented HBAC-AVOR… More >

  • Open Access

    ARTICLE

    Locomotion of Bioinspired Underwater Snake Robots Using Metaheuristic Algorithm

    Souad Larabi-Marie-Sainte1, Taiseer Abdalla Elfadil Eisa2, Fahd N. Al-Wesabi3,4, Amani Abdulrahman Albraikan5, Manar Ahmed Hamza6,*, Abdelwahed Motwakel6, Ishfaq Yaseen6, Mesfer Al Duhayyim7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1293-1308, 2022, DOI:10.32604/cmc.2022.024585 - 24 February 2022

    Abstract Snake Robots (SR) have been successfully deployed and proved to attain bio-inspired solutions owing to its capability to move in harsh environments, a characteristic not found in other kinds of robots (like wheeled or legged robots). Underwater Snake Robots (USR) establish a bioinspired solution in the domain of underwater robotics. It is a key challenge to increase the motion efficiency in underwater robots, with respect to forwarding speed, by enhancing the locomotion method. At the same time, energy efficiency is also considered as a crucial issue for long-term automation of the systems. In this aspect,… More >

  • Open Access

    ARTICLE

    Crow Search Algorithm with Improved Objective Function for Test Case Generation and Optimization

    Meena Sharma, Babita Pathik*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1125-1140, 2022, DOI:10.32604/iasc.2022.022335 - 17 November 2021

    Abstract Test case generation and optimization is the foremost requirement of software evolution and test automation. In this paper, a bio-inspired Crow Search Algorithm (CSA) is suggested with an improved objective function to fulfill this requirement. CSA is a nature-inspired optimization method. The improved objective function combines branch distance and predicate distance to cover the critical path on the control flow graph. CSA is a search-based technique that uses heuristic information for automation testing, and CSA optimizers minimize test cases generated by satisfying the objective function. This paper focuses on generating test cases for all paths,… More >

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