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  • Open Access


    Intelligent Deer Hunting Optimization Based Grid Scheduling Scheme

    Mesfer Al Duhayyim1, Majdy M. Eltahir2, Imène Issaoui3, Fahd N. Al-Wesabi2,4, Anwer Mustafa Hilal5, Fuad Ali Mohammed Al-Yarimi2, Manar Ahmed Hamza5,*, Abu Sarwar Zamani5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 181-195, 2022, DOI:10.32604/cmc.2022.024206

    Abstract The grid environment is a dynamic, heterogeneous, and changeable computing system that distributes various services amongst different clients. To attain the benefits of collaborative resource sharing in Grid computing, a novel and proficient grid resource management system (RMS) is essential. Therefore, detection of an appropriate resource for the presented task is a difficult task. Several scientists have presented algorithms for mapping tasks to the resource. Few of them focus on fault tolerance, user fulfillment, and load balancing. With this motivation, this study designs an intelligent grid scheduling scheme using deer hunting optimization algorithm (DHOA), called More >

  • Open Access


    Hybrid Cuckoo Search Algorithm for Scheduling in Cloud Computing

    Manoj Kumar*, Suman

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1641-1660, 2022, DOI:10.32604/cmc.2022.021793

    Abstract Cloud computing has gained widespread popularity over the last decade. Scheduling problem in cloud computing is prejudiced due to enormous demands of cloud users. Meta-heuristic techniques in cloud computing have exhibited high performance in comparison to traditional scheduling algorithms. This paper presents a novel hybrid Nesterov Accelerated Gradient-based Cuckoo Search Algorithm (NAGCSA) to address the scheduling issue in cloud computing. Nesterov Accelerated Gradient can address trapping at local minima in CSA by updating the position using future approximation. The local search in the proposed algorithm is performed by using Nesterov Accelerated Gradient, while the global More >

  • Open Access


    A Hybrid Model for Reliability Aware and Energy-Efficiency in Multicore Systems

    Samar Nour1,*, Sameh A. Salem1,2, Shahira M. Habashy1

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4447-4466, 2022, DOI:10.32604/cmc.2022.020775

    Abstract Recently, Multicore systems use Dynamic Voltage/Frequency Scaling (DV/FS) technology to allow the cores to operate with various voltage and/or frequencies than other cores to save power and enhance the performance. In this paper, an effective and reliable hybrid model to reduce the energy and makespan in multicore systems is proposed. The proposed hybrid model enhances and integrates the greedy approach with dynamic programming to achieve optimal Voltage/Frequency (Vmin/F) levels. Then, the allocation process is applied based on the available workloads. The hybrid model consists of three stages. The first stage gets the optimum safe voltage More >

  • Open Access


    Scheduling Flexible Flow Shop in Labeling Companies to Minimize the Makespan

    Chia-Nan Wang1, Hsien-Pin Hsu2, Hsin-Pin Fu3,*, Nguyen Ky Phuc Phan4, Van Thanh Nguyen5

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 17-36, 2022, DOI:10.32604/csse.2022.016992

    Abstract In the competitive global marketplace, production scheduling plays a vital role in planning in manufacturing. Scheduling deals directly with the time to output products quickly and with a low production cost. This research examines case study of a Radio-Frequency Identification labeling department at Avery Dennison. The main objective of the company is to have a method that allows for the sequencing and scheduling of a set of jobs so it can be completed on or before the customer’s due date to minimize the number of late orders. This study analyzes the flexible flow shop scheduling More >

  • Open Access


    Monarch Butterfly Optimization for Reliable Scheduling in Cloud

    B. Gomathi1, S. T. Suganthi2,*, Karthikeyan Krishnasamy3, J. Bhuvana4

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3693-3710, 2021, DOI:10.32604/cmc.2021.018159

    Abstract Enterprises have extensively taken on cloud computing environment since it provides on-demand virtualized cloud application resources. The scheduling of the cloud tasks is a well-recognized NP-hard problem. The Task scheduling problem is convoluted while convincing different objectives, which are dispute in nature. In this paper, Multi-Objective Improved Monarch Butterfly Optimization (MOIMBO) algorithm is applied to solve multi-objective task scheduling problems in the cloud in preparation for Pareto optimal solutions. Three different dispute objectives, such as makespan, reliability, and resource utilization, are deliberated for task scheduling problems.The Epsilon-fuzzy dominance sort method is utilized in the multi-objective More >

  • Open Access


    A Compromise Programming to Task Assignment Problem in Software Development Project

    Ngo Tung Son1,2,*, Jafreezal Jaafar1, Izzatdin Abdul Aziz1, Bui Ngoc Anh2, Hoang Duc Binh2, Muhammad Umar Aftab3

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3429-3444, 2021, DOI:10.32604/cmc.2021.017710

    Abstract The scheduling process that aims to assign tasks to members is a difficult job in project management. It plays a prerequisite role in determining the project’s quality and sometimes winning the bidding process. This study aims to propose an approach based on multi-objective combinatorial optimization to do this automatically. The generated schedule directs the project to be completed with the shortest critical path, at the minimum cost, while maintaining its quality. There are several real-world business constraints related to human resources, the similarity of the tasks added to the optimization model, and the literature’s traditional… More >

  • Open Access


    Fault Aware Dynamic Resource Manager for Fault Recognition and Avoidance in Cloud

    Nandhini Jembu Mohanram1,2,*, Gnanasekaran Thangavel3, N. M. Jothi Swaroopan4

    Computer Systems Science and Engineering, Vol.38, No.2, pp. 215-228, 2021, DOI:10.32604/csse.2021.015027

    Abstract Fault tolerance (FT) schemes are intended to work on a minimized and static amount of physical resources. When a host failure occurs, the conventional FT frequently proceeds with the execution on the accessible working hosts. This methodology saves the execution state and applications to complete without disruption. However, the dynamicity of open cloud assets is not seen when taking scheduling choices. Existing optimization techniques are intended in dealing with resource scheduling. This method will be utilized for distributing the approaching tasks to the VMs. However, the dynamic scheduling for this procedure doesn’t accomplish the objective… More >

  • Open Access


    A Load Balanced Task Scheduling Heuristic for Large-Scale Computing Systems

    Sardar Khaliq uz Zaman1, Tahir Maqsood1, Mazhar Ali1, Kashif Bilal1, Sajjad A. Madani1, Atta ur Rehman Khan2,*

    Computer Systems Science and Engineering, Vol.34, No.2, pp. 79-90, 2019, DOI:10.32604/csse.2019.34.079

    Abstract Optimal task allocation in Large-Scale Computing Systems (LSCSs) that endeavors to balance the load across limited computing resources is considered an NP-hard problem. MinMin algorithm is one of the most widely used heuristic for scheduling tasks on limited computing resources. The MinMin minimizes makespan compared to other algorithms, such as Heterogeneous Earliest Finish Time (HEFT), duplication based algorithms, and clustering algorithms. However, MinMin results in unbalanced utilization of resources especially when majority of tasks have lower computational requirements. In this work we consider a computational model where each machine has certain bounded capacity to execute… More >

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