☆ 4.7 Article

A dynamic multipopulation genetic algorithm for multiobjective workflow scheduling based on the longest common sequence

SWARM AND EVOLUTIONARY COMPUTATION (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Software Engineering

Energy and cost aware workflow scheduling in clouds with deadline constraint

Rambabu Medara et al.

Summary: Cloud computing is a promising platform for executing complex scientific workflow applications. Efficient task scheduling in clouds is critical, as it directly affects energy utilization and execution cost. This article presents an energy and cost-aware scheduling approach, which was evaluated using the WorkflowSim tool and demonstrated significant energy conservation and cost reduction compared to existing algorithms.

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE (2022)

添加到收藏夹

Article Computer Science, Information Systems

Scheduling Workflows With Composite Tasks: A Nested Particle Swarm Optimization Approach

An Song et al.

Summary: This article proposes a novel workflow model with composite tasks, which can manage complex workflows and address data transmission between sub-tasks. To solve this problem, a nested particle swarm optimization and a fast version of nested particle swarm optimization are devised.

IEEE TRANSACTIONS ON SERVICES COMPUTING (2022)

添加到收藏夹

Article Computer Science, Information Systems

Multi-objective workflow scheduling based on genetic algorithm in cloud environment

Xuewen Xia et al.

Summary: In this paper, a multi-objective genetic algorithm (MOGA) is proposed and applied to optimize workflow scheduling problems under the cloud computing environment. An initialization scheduling sequence scheme is introduced to enhance search efficiency, and the longest common subsequence (LCS) is integrated into the genetic algorithm (GA) to achieve a balance between exploration and exploitation. Experimental results demonstrate that the proposed GALCS algorithm outperforms ordinary GA and other state-of-the-art algorithms in finding a better Pareto front.

INFORMATION SCIENCES (2022)

添加到收藏夹

Article Telecommunications

A Predictive Energy Consumption Scheduling Algorithm for Multiprocessor Heterogeneous System

Shujuan Tian et al.

Summary: With the growing number of users and applications in the era of Industrial Internet of Things (I-IoT), improving computing efficiency and reducing energy consumption are crucial. This paper proposes a Predictive Energy Consumption Scheduling (PECS) algorithm to match the frequency for each task, resulting in significant energy savings compared to other state-of-the-art algorithms.

IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING (2022)

添加到收藏夹

Article Computer Science, Information Systems

DCHG-TS: a deadline-constrained and cost-effective hybrid genetic algorithm for scientific workflow scheduling in cloud computing

Amir Iranmanesh et al.

Summary: This study presents an approach to workflow task scheduling based on genetic algorithms, which utilizes new genetic operators and load balancing routines to enhance efficiency in cloud environments. Results demonstrate that the proposed algorithm outperforms state-of-the-art methods in task scheduling, achieving shorter makespan and lower cost.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Many-objective cloud manufacturing service selection and scheduling with an evolutionary algorithm based on adaptive environment selection strategy

Tianri Wang et al.

Summary: This paper investigates the Cloud Manufacturing Service Selection and Scheduling (CMSSS) problem, constructs an eight-objective optimization model, and designs a many-objective evolutionary algorithm MaOEA-AES to address the issue. By using diversity-based population partition technology and adaptive penalty boundary intersection distance, the algorithm maintains population diversity and selects elitist solutions effectively.

APPLIED SOFT COMPUTING (2021)

添加到收藏夹

Article Computer Science, Information Systems

A fitness-based adaptive differential evolution algorithm

Xuewen Xia et al.

Summary: The paper introduces a fitness-based adaptive differential evolution algorithm (FADE) that splits the population into multiple small-sized swarms and uses an archive of breeding strategies, allowing individuals within the same swarm to adaptively select their own strategy based on fitness. By adaptively adjusting population size and allocating computational resources based on performance, FADE can effectively address diverse fitness landscapes and achieve distinct search behaviors within each swarm. The effectiveness and efficiency of the newly introduced adaptive strategies are confirmed through comprehensive evaluations and comparisons with other state-of-art DE variants.

INFORMATION SCIENCES (2021)

添加到收藏夹

Article Computer Science, Information Systems

A hybrid multi-objective metaheuristic optimization algorithm for scientific workflow scheduling

Ali Mohammadzadeh et al.

Summary: The study focused on workflow scheduling in the cloud environment and proposed a meta-heuristic algorithm combining the ant lion optimizer with the Sine Cosine Algorithm to address multiple objectives. The optimization strategy aimed to reduce energy consumption and makespan, achieve a green cloud environment, and increase throughput.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2021)

添加到收藏夹

Article Computer Science, Hardware & Architecture

Makespan-Cost-Reliability-Optimized Workflow Scheduling Using Evolutionary Techniques in Clouds

Xiumin Zhou et al.

JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS (2020)

添加到收藏夹

Article Automation & Control Systems

MOELS: Multiobjective Evolutionary List Scheduling for Cloud Workflows

Quanwang Wu et al.

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2020)

添加到收藏夹

Article Computer Science, Theory & Methods

GRP-HEFT: A Budget-Constrained Resource Provisioning Scheme for Workflow Scheduling in IaaS Clouds

Hamid Reza Faragardi et al.

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

A hybrid genetic algorithm for scientific workflow scheduling in cloud environment

Hatem Aziza et al.

NEURAL COMPUTING & APPLICATIONS (2020)

添加到收藏夹

Article Computer Science, Theory & Methods

Q-learning based dynamic task scheduling for energy-efficient cloud computing

Ding Ding et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2020)

添加到收藏夹

Article Automation & Control Systems

Dynamic Group Learning Distributed Particle Swarm Optimization for Large-Scale Optimization and Its Application in Cloud Workflow Scheduling

Zi-Jia Wang et al.

IEEE TRANSACTIONS ON CYBERNETICS (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Multiple adaptive strategies based particle swarm optimization algorithm

Bo Wei et al.

SWARM AND EVOLUTIONARY COMPUTATION (2020)

添加到收藏夹

Article Automation & Control Systems

Multiobjective Cloud Workflow Scheduling: A Multiple Populations Ant Colony System Approach

Zong-Gan Chen et al.

IEEE TRANSACTIONS ON CYBERNETICS (2019)

添加到收藏夹

Article Computer Science, Information Systems

Reliability and energy efficient workflow scheduling in cloud environment

Ritu Garg et al.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2019)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Genetic-based Multi-criteria Workflow Scheduling with Dynamic Resource Provisioning in Hybrid Large Scale Distributed Systems

Haithem Hafsi et al.

KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES 2019) (2019)

添加到收藏夹

Article Computer Science, Information Systems

Workflow Scheduling Using Hybrid GA-PSO Algorithm in Cloud Computing

Ahmad M. Manasrah et al.

WIRELESS COMMUNICATIONS & MOBILE COMPUTING (2018)

添加到收藏夹

Article Computer Science, Theory & Methods

A hybrid multi-objective Particle Swarm Optimization for scientific workflow scheduling

Amandeep Verma et al.

PARALLEL COMPUTING (2017)

添加到收藏夹

Article Automation & Control Systems

Diversity Assessment in Many-Objective Optimization

Handing Wang et al.

IEEE TRANSACTIONS ON CYBERNETICS (2017)

添加到收藏夹

Article Computer Science, Theory & Methods

Evolutionary Multi-Objective Workflow Scheduling in Cloud

Zhaomeng Zhu et al.

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2016)

添加到收藏夹

Article Computer Science, Hardware & Architecture

Cost Adaptive VM Management for Scientific Workflow Application in Mobile Cloud

Woo-Joong Kim et al.

MOBILE NETWORKS & APPLICATIONS (2015)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Multiobjective firefly algorithm for continuous optimization

Xin-She Yang

ENGINEERING WITH COMPUTERS (2013)

添加到收藏夹

Article Computer Science, Theory & Methods

Characterizing and profiling scientific workflows

Gideon Juve et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2013)

添加到收藏夹

Article Computer Science, Theory & Methods

Deadline-constrained workflow scheduling algorithms for Infrastructure as a Service Clouds

Saeid Abrishami et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2013)

添加到收藏夹

Article Computer Science, Theory & Methods

Cost-efficient task scheduling for executing large programs in the cloud

Sen Su et al.

PARALLEL COMPUTING (2013)

添加到收藏夹

Article Computer Science, Hardware & Architecture

Enforcing QoS in scientific workflow systems enacted over Cloud infrastructures

Rafael Tolosana-Calasanza et al.

JOURNAL OF COMPUTER AND SYSTEM SCIENCES (2012)

添加到收藏夹

Article Computer Science, Software Engineering

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

Rodrigo N. Calheiros et al.

SOFTWARE-PRACTICE & EXPERIENCE (2011)

添加到收藏夹

Article Mathematics, Applied

A comparative study of Artificial Bee Colony algorithm

Dervis Karaboga et al.

APPLIED MATHEMATICS AND COMPUTATION (2009)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II

Hui Li et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2009)

添加到收藏夹

Article Computer Science, Theory & Methods

Performance-effective and low-complexity task scheduling for heterogeneous computing

H Topcuoglu et al.

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2002)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.