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Search Results (14)
  • 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

    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 study introduces a Battle Royale… More >

  • 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

    Oppositional Red Fox Optimization Based Task Scheduling Scheme for Cloud Environment

    B. Chellapraba1,*, D. Manohari2, K. Periyakaruppan3, M. S. Kavitha4

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 483-495, 2023, DOI:10.32604/csse.2023.029854

    Abstract Owing to massive technological developments in Internet of Things (IoT) and cloud environment, cloud computing (CC) offers a highly flexible heterogeneous resource pool over the network, and clients could exploit various resources on demand. Since IoT-enabled models are restricted to resources and require crisp response, minimum latency, and maximum bandwidth, which are outside the capabilities. CC was handled as a resource-rich solution to aforementioned challenge. As high delay reduces the performance of the IoT enabled cloud platform, efficient utilization of task scheduling (TS) reduces the energy usage of the cloud infrastructure and increases the income of service provider via minimizing… More >

  • Open Access

    ARTICLE

    An Adaptive Genetic Algorithm-Based Load Balancing-Aware Task Scheduling Technique for Cloud Computing

    Mohit Agarwal1,*, Shikha Gupta2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6103-6119, 2022, DOI:10.32604/cmc.2022.030778

    Abstract Task scheduling in highly elastic and dynamic processing environments such as cloud computing have become the most discussed problem among researchers. Task scheduling algorithms are responsible for the allocation of the tasks among the computing resources for their execution, and an inefficient task scheduling algorithm results in under-or over-utilization of the resources, which in turn leads to degradation of the services. Therefore, in the proposed work, load balancing is considered as an important criterion for task scheduling in a cloud computing environment as it can help in reducing the overhead in the critical decision-oriented process. In this paper, we propose… More >

  • Open Access

    ARTICLE

    Hybridization of Metaheuristics Based Energy Efficient Scheduling Algorithm for Multi-Core Systems

    J. Jean Justus1, U. Sakthi2, K. Priyadarshini3, B. Thiyaneswaran4, Masoud Alajmi5, Marwa Obayya6, Manar Ahmed Hamza7,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 205-219, 2023, DOI:10.32604/csse.2023.025256

    Abstract The developments of multi-core systems (MCS) have considerably improved the existing technologies in the field of computer architecture. The MCS comprises several processors that are heterogeneous for resource capacities, working environments, topologies, and so on. The existing multi-core technology unlocks additional research opportunities for energy minimization by the use of effective task scheduling. At the same time, the task scheduling process is yet to be explored in the multi-core systems. This paper presents a new hybrid genetic algorithm (GA) with a krill herd (KH) based energy-efficient scheduling technique for multi-core systems (GAKH-SMCS). The goal of the GAKH-SMCS technique is to… More >

  • Open Access

    ARTICLE

    Hybrid Invasive Weed Improved Grasshopper Optimization Algorithm for Cloud Load Balancing

    K. Naveen Durai*, R. Subha, Anandakumar Haldorai

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 467-483, 2022, DOI:10.32604/iasc.2022.026020

    Abstract In cloud computing, the processes of load balancing and task scheduling are major concerns as they are the primary mechanisms responsible for executing tasks by allocating and utilizing the resources of Virtual Machines (VMs) in a more optimal way. This problem of balancing loads and scheduling tasks in the cloud computing scenario can be categorized as an NP-hard problem. This problem of load balancing needs to be efficiently allocated tasks to VMs and sustain the trade-off among the complete set of VMs. It also needs to maintain equilibrium among VMs with the objective of maximizing throughput with a minimized time… More >

  • Open Access

    ARTICLE

    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 IGSS-DHOA which schedules in such… More >

  • Open Access

    ARTICLE

    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 search is performed by using… More >

  • Open Access

    ARTICLE

    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 while the second stage sets… More >

  • Open Access

    ARTICLE

    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 problem with a sequence dependent… More >

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