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Search Results (15)
  • Open Access

    ARTICLE

    A Novel Optimization Approach for Energy-Efficient Multiple Workflow Scheduling in Cloud Environment

    Ambika Aggarwal1, Sunil Kumar2,3, Ashok Bhansali4, Deema Mohammed Alsekait5,*, Diaa Salama AbdElminaam6,7,8

    Computer Systems Science and Engineering, Vol.48, No.4, pp. 953-967, 2024, DOI:10.32604/csse.2024.050406 - 17 July 2024

    Abstract Existing multiple workflow scheduling techniques focus on traditional Quality of Service (QoS) parameters such as cost, deadline, and makespan to find optimal solutions by consuming a large amount of electrical energy. Higher energy consumption decreases system efficiency, increases operational cost, and generates more carbon footprint. These major problems can lead to several problems, such as economic strain, environmental degradation, resource depletion, energy dependence, health impacts, etc. In a cloud computing environment, scheduling multiple workflows is critical in developing a strategy for energy optimization, which is an NP-hard problem. This paper proposes a novel, bi-phase Energy-Efficient… More >

  • Open Access

    ARTICLE

    Distributed Graph Database Load Balancing Method Based on Deep Reinforcement Learning

    Shuming Sha1,2, Naiwang Guo3, Wang Luo1,2, Yong Zhang1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5105-5124, 2024, DOI:10.32604/cmc.2024.049584 - 20 June 2024

    Abstract This paper focuses on the scheduling problem of workflow tasks that exhibit interdependencies. Unlike independent batch tasks, workflows typically consist of multiple subtasks with intrinsic correlations and dependencies. It necessitates the distribution of various computational tasks to appropriate computing node resources in accordance with task dependencies to ensure the smooth completion of the entire workflow. Workflow scheduling must consider an array of factors, including task dependencies, availability of computational resources, and the schedulability of tasks. Therefore, this paper delves into the distributed graph database workflow task scheduling problem and proposes a workflow scheduling methodology based… More >

  • Open Access

    ARTICLE

    Improved Harris Hawks Optimization Algorithm Based Data Placement Strategy for Integrated Cloud and Edge Computing

    V. Nivethitha*, G. Aghila

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 887-904, 2023, DOI:10.32604/iasc.2023.034247 - 29 April 2023

    Abstract Cloud computing is considered to facilitate a more cost-effective way to deploy scientific workflows. The individual tasks of a scientific workflow necessitate a diversified number of large states that are spatially located in different datacenters, thereby resulting in huge delays during data transmission. Edge computing minimizes the delays in data transmission and supports the fixed storage strategy for scientific workflow private datasets. Therefore, this fixed storage strategy creates huge amount of bottleneck in its storage capacity. At this juncture, integrating the merits of cloud computing and edge computing during the process of rationalizing the data… More >

  • Open Access

    ARTICLE

    AWSD: An Aircraft Wing Dataset Created by an Automatic Workflow for Data Mining in Geometric Processing

    Xiang Su1, Nan Li1,*, Yuedi Hu1, Haisheng Li2

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2935-2956, 2023, DOI:10.32604/cmes.2023.026083 - 09 March 2023

    Abstract This paper introduces an aircraft wing simulation data set (AWSD) created by an automatic workflow based on creating models, meshing, simulating the wing flight flow field solution, and parameterizing solution results. AWSD is a flexible, independent wing collection of simulations with specific engineering requirements. The data set is applicable to handle computer geometry processing tasks. In contrast to the existing 3D model data set, there are some advantages the scale of this data set is not limited by the collection source, the data files have high quality, no defects, redundancy, and other problems, and the… More > Graphic Abstract

    AWSD: An Aircraft Wing Dataset Created by an Automatic Workflow for Data Mining in Geometric Processing

  • Open Access

    REVIEW

    Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

    Qiqi Zhang1, Shaojin Geng2, Xingjuan Cai1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 1863-1900, 2023, DOI:10.32604/cmes.2023.022287 - 23 November 2022

    Abstract Cloud computing technology is favored by users because of its strong computing power and convenient services. At the same time, scheduling performance has an extremely efficient impact on promoting carbon neutrality. Currently, scheduling research in the multi-cloud environment aims to address the challenges brought by business demands to cloud data centers during peak hours. Therefore, the scheduling problem has promising application prospects under the multi-cloud environment. This paper points out that the currently studied scheduling problems in the multi-cloud environment mainly include independent task scheduling and workflow task scheduling based on the dependencies between tasks. More > Graphic Abstract

    Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

  • Open Access

    ARTICLE

    Failure Prediction for Scientific Workflows Using Nature-Inspired Machine Learning Approach

    S. Sridevi*, Jeevaa Katiravan

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 223-233, 2023, DOI:10.32604/iasc.2023.031928 - 29 September 2022

    Abstract Scientific workflows have gained the emerging attention in sophisticated large-scale scientific problem-solving environments. The pay-per-use model of cloud, its scalability and dynamic deployment enables it suited for executing scientific workflow applications. Since the cloud is not a utopian environment, failures are inevitable that may result in experiencing fluctuations in the delivered performance. Though a single task failure occurs in workflow based applications, due to its task dependency nature, the reliability of the overall system will be affected drastically. Hence rather than reactive fault-tolerant approaches, proactive measures are vital in scientific workflows. This work puts forth… More >

  • Open Access

    ARTICLE

    Efficient Computation Offloading of IoT-Based Workflows Using Discrete Teaching Learning-Based Optimization

    Mohamed K. Hussein1,*, Mohamed H. Mousa1,2

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3685-3703, 2022, DOI:10.32604/cmc.2022.026370 - 16 June 2022

    Abstract As the Internet of Things (IoT) and mobile devices have rapidly proliferated, their computationally intensive applications have developed into complex, concurrent IoT-based workflows involving multiple interdependent tasks. By exploiting its low latency and high bandwidth, mobile edge computing (MEC) has emerged to achieve the high-performance computation offloading of these applications to satisfy the quality-of-service requirements of workflows and devices. In this study, we propose an offloading strategy for IoT-based workflows in a high-performance MEC environment. The proposed task-based offloading strategy consists of an optimization problem that includes task dependency, communication costs, workflow constraints, device energy More >

  • Open Access

    ARTICLE

    Weighted-adaptive Inertia Strategy for Multi-objective Scheduling in Multi-clouds

    Mazen Farid1,3,*, Rohaya Latip1,2, Masnida Hussin1, Nor Asilah Wati Abdul Hamid1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1529-1560, 2022, DOI:10.32604/cmc.2022.021410 - 24 February 2022

    Abstract One of the fundamental problems associated with scheduling workflows on virtual machines in a multi-cloud environment is how to find a near-optimum permutation. The workflow scheduling involves assigning independent computational jobs with conflicting objectives to a set of virtual machines. Most optimization methods for solving non-deterministic polynomial-time hardness (NP-hard) problems deploy multi-objective algorithms. As such, Pareto dominance is one of the most efficient criteria for determining the best solutions within the Pareto front. However, the main drawback of this method is that it requires a reasonably long time to provide an optimum solution. In this… More >

  • Open Access

    ARTICLE

    Rapid Profiling and Characterization of the Multicomponents from the Root and Rhizome of Salvia miltiorrhiza by Ultra-High Performance Liquid Chromatography/Ion Mobility-Quadrupole Time-of-Flight Mass Spectrometry in Combination with Computational Peak Annotation Workflows

    Boxue Chen1,#, Hongda Wang1,#, Meiyu Liu1, Wandi Hu1, Yuexin Qian1, Jiali Wang1, Jie Liu1, Xue Li1, Jing Wang2, Wenzhi Yang1,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.5, pp. 1073-1088, 2022, DOI:10.32604/phyton.2022.019399 - 24 January 2022

    Abstract Herbal components characterization represents a challenging task because of the co-existing of multiple classes of naturally occurring compounds with wide spans of polarity, molecular mass, and the ubiquitous isomerism. The root and rhizome of Salvia miltiorrhiza have been utilized as a reputable traditional Chinese medicine Salviae Miltiorrhizae Radix et Rhizoma (Dan-Shen) in the treatment of cardiovascular disease. Herein, a dimension-enhanced ultra-high performance liquid chromatography/ion mobility/quadrupole time-of-flight mass spectrometry approach in combination with intelligent peak annotation workflows was established aimed to rapidly characterize the multicomponents from S. miltiorrhiza. Due to the sufficient optimization, satisfactory chromatography separation was enabled… More >

  • Open Access

    ARTICLE

    CMMI Compliant Workflow Models to Track and Control Changes

    Islam Ali1, Syed Muhammad Ali1, Waqar Mehmood2, Wasif Nisar1, Muhammad Qaiser Saleem3, Majzoob K. Omer3, Mahmood Niazi4, Muhammad Shafiq5, Jin-Ghoo Choi5,*

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 387-405, 2022, DOI:10.32604/iasc.2022.015955 - 03 September 2021

    Abstract The Capability Maturity Model Integration (CMMI) is a renowned Software Process Improvement (SPI) framework. Research studies have revealed that CMMI adoption needs a lot of resources in terms of training, funds, and professional workers. However, the software SMEs (SSMEs) have few resources and cannot adopt CMMI. One of the challenges of adopting CMMI is that CMMI tells “What to do?” as requirements to be met, and leaves “How to do?” to the implementers. The software industry especially SSMEs faces difficulties in successfully implementing various process areas (PAs) particularly Configuration Management Process Area (CM-PA). SG-2 (Track… More >

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