Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (19)
  • Open Access

    ARTICLE

    A Pre-Selection-Based Ant Colony System for Integrated Resources Scheduling Problem at Marine Container Terminal

    Rong Wang1, Xinxin Xu2, Zijia Wang3,*, Fei Ji1, Nankun Mu4

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2363-2385, 2024, DOI:10.32604/cmc.2024.053564 - 15 August 2024

    Abstract Marine container terminal (MCT) plays a key role in the marine intelligent transportation system and international logistics system. However, the efficiency of resource scheduling significantly influences the operation performance of MCT. To solve the practical resource scheduling problem (RSP) in MCT efficiently, this paper has contributions to both the problem model and the algorithm design. Firstly, in the problem model, different from most of the existing studies that only consider scheduling part of the resources in MCT, we propose a unified mathematical model for formulating an integrated RSP. The new integrated RSP model allocates and… More >

  • Open Access

    ARTICLE

    Dynamic Offloading and Scheduling Strategy for Telematics Tasks Based on Latency Minimization

    Yu Zhou1, Yun Zhang1, Guowei Li1, Hang Yang1, Wei Zhang1, Ting Lyu2, Yueqiang Xu2,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1809-1829, 2024, DOI:10.32604/cmc.2024.050975 - 15 August 2024

    Abstract In current research on task offloading and resource scheduling in vehicular networks, vehicles are commonly assumed to maintain constant speed or relatively stationary states, and the impact of speed variations on task offloading is often overlooked. It is frequently assumed that vehicles can be accurately modeled during actual motion processes. However, in vehicular dynamic environments, both the tasks generated by the vehicles and the vehicles’ surroundings are constantly changing, making it difficult to achieve real-time modeling for actual dynamic vehicular network scenarios. Taking into account the actual dynamic vehicular scenarios, this paper considers the real-time… More >

  • Open Access

    ARTICLE

    Research on Flexible Job Shop Scheduling Based on Improved Two-Layer Optimization Algorithm

    Qinhui Liu, Laizheng Zhu, Zhijie Gao, Jilong Wang, Jiang Li*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 811-843, 2024, DOI:10.32604/cmc.2023.046040 - 30 January 2024

    Abstract To improve the productivity, the resource utilization and reduce the production cost of flexible job shops, this paper designs an improved two-layer optimization algorithm for the dual-resource scheduling optimization problem of flexible job shop considering workpiece batching. Firstly, a mathematical model is established to minimize the maximum completion time. Secondly, an improved two-layer optimization algorithm is designed: the outer layer algorithm uses an improved PSO (Particle Swarm Optimization) to solve the workpiece batching problem, and the inner layer algorithm uses an improved GA (Genetic Algorithm) to solve the dual-resource scheduling problem. Then, a rescheduling method… More >

  • Open Access

    ARTICLE

    A Novel Predictive Model for Edge Computing Resource Scheduling Based on Deep Neural Network

    Ming Gao1,#, Weiwei Cai1,#, Yizhang Jiang1, Wenjun Hu3, Jian Yao2, Pengjiang Qian1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 259-277, 2024, DOI:10.32604/cmes.2023.029015 - 30 December 2023

    Abstract Currently, applications accessing remote computing resources through cloud data centers is the main mode of operation, but this mode of operation greatly increases communication latency and reduces overall quality of service (QoS) and quality of experience (QoE). Edge computing technology extends cloud service functionality to the edge of the mobile network, closer to the task execution end, and can effectively mitigate the communication latency problem. However, the massive and heterogeneous nature of servers in edge computing systems brings new challenges to task scheduling and resource management, and the booming development of artificial neural networks provides More >

  • Open Access

    ARTICLE

    Efficient Cloud Resource Scheduling with an Optimized Throttled Load Balancing Approach

    V. Dhilip Kumar1, J. Praveenchandar2, Muhammad Arif3,*, Adrian Brezulianu4, Oana Geman5, Atif Ikram3,6

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2179-2188, 2023, DOI:10.32604/cmc.2023.034764 - 29 November 2023

    Abstract Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage, processing power, and other computer system resources. It is also referred to as a system that will let the consumers utilize computational resources like databases, servers, storage, and intelligence over the Internet. In a cloud network, load balancing is the process of dividing network traffic among a cluster of available servers to increase efficiency. It is also known as a server pool or server farm. When a single node is overwhelmed, balancing the workload is needed to manage unpredictable workflows. The More >

  • Open Access

    ARTICLE

    Research on Optimization of Dual-Resource Batch Scheduling in Flexible Job Shop

    Qinhui Liu, Zhijie Gao, Jiang Li*, Shuo Li, Laizheng Zhu

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2503-2530, 2023, DOI:10.32604/cmc.2023.040505 - 30 August 2023

    Abstract With the rapid development of intelligent manufacturing and the changes in market demand, the current manufacturing industry presents the characteristics of multi-varieties, small batches, customization, and a short production cycle, with the whole production process having certain flexibility. In this paper, a mathematical model is established with the minimum production cycle as the optimization objective for the dual-resource batch scheduling of the flexible job shop, and an improved nested optimization algorithm is designed to solve the problem. The outer layer batch optimization problem is solved by the improved simulated annealing algorithm. The inner double resource More >

  • Open Access

    ARTICLE

    Battle Royale Optimization-Based Resource Scheduling Scheme for Cloud Computing Environment

    Lenin Babu Russeliah1,*, R. Adaline Suji2, D. Bright Anand3

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3925-3938, 2023, DOI:10.32604/csse.2023.034727 - 03 April 2023

    Abstract Cloud computing (CC) is developing as a powerful and flexible computational structure for providing ubiquitous service to users. It receives interrelated software and hardware resources in an integrated manner distinct from the classical computational environment. The variation of software and hardware resources were combined and composed as a resource pool. The software no more resided in the single hardware environment, it can be executed on the schedule of resource pools to optimize resource consumption. Optimizing energy consumption in CC environments is the question that allows utilizing several energy conservation approaches for effective resource allocation. This… More >

  • Open Access

    ARTICLE

    Formal Modeling of Self-Adaptive Resource Scheduling in Cloud

    Atif Ishaq Khan*, Syed Asad Raza Kazmi, Awais Qasim

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1183-1197, 2023, DOI:10.32604/cmc.2023.032691 - 22 September 2022

    Abstract A self-adaptive resource provisioning on demand is a critical factor in cloud computing. The selection of accurate amount of resources at run time is not easy due to dynamic nature of requests. Therefore, a self-adaptive strategy of resources is required to deal with dynamic nature of requests based on run time change in workload. In this paper we proposed a Cloud-based Adaptive Resource Scheduling Strategy (CARSS) Framework that formally addresses these issues and is more expressive than traditional approaches. The decision making in CARSS is based on more than one factors. The MAPE-K based framework More >

  • Open Access

    ARTICLE

    OFDM-CFO and Resource Scheduling Algorithm Using Fuzzy Linear-CFO

    M. Prabhu1,*, B. Muthu Kumar2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2513-2525, 2023, DOI:10.32604/iasc.2023.027823 - 19 July 2022

    Abstract Orthogonal Frequency-Division Multiplexing (OFDM) is the form of a digital system and a way of encoding digital data across multiple frequency components that are used in telecommunication services. Carrier Frequency Offset (CFO) inaccuracy is a major disadvantage of OFDM. This paper proposed a feasible and elegant fuzzy-based resource allocation technique, that overcomes the constraints of the CFO. The suggested Fuzzy linear CFO estimation (FL-CFO) not only estimates the CFO with increased precision but also allocates resources effectively, and achieves maximum utilization of dynamic resources. The suggested FL-CFO error estimation algorithm in OFDM systems employing 1-bit… More >

  • Open Access

    ARTICLE

    Chaotic Sandpiper Optimization Based Virtual Machine Scheduling for Cyber-Physical Systems

    P. Ramadevi1,*, T. Jayasankar1, V. Dinesh2, M. Dhamodaran3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1373-1385, 2023, DOI:10.32604/csse.2023.026603 - 15 June 2022

    Abstract Recently, with the growth of cyber physical systems (CPS), several applications have begun to deploy in the CPS for connecting the cyber space with the physical scale effectively. Besides, the cloud computing (CC) enabled CPS offers huge processing and storage resources for CPS that finds helpful for a range of application areas. At the same time, with the massive development of applications that exist in the CPS environment, the energy utilization of the cloud enabled CPS has gained significant interest. For improving the energy effectiveness of the CC platform, virtualization technologies have been employed for… More >

Displaying 1-10 on page 1 of 19. Per Page