☆ 4.5 Article

Energy-efficient virtual machine placement in distributed cloud using NSGA-III algorithm

JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS (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

Experimental performance analysis of cloud resource allocation framework using spider monkey optimization algorithm

Mohit Kumar et al.

Summary: The demand for cloud services has exponentially increased, leading to the need for efficient resource allocation. This article presents a secure and self-adaptive resource allocation framework that utilizes the enhanced spider monkey optimization algorithm to address the issue.

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE (2023)

添加到收藏夹

Article Computer Science, Information Systems

Multi-Objective Grey Wolf Optimizer Algorithm for Task Scheduling in Cloud-Fog Computing

Faten A. Saif et al.

Summary: The revolution of IoT has generated a large amount of data for processing in various fields. Instant response tasks are sent to the fog node due to its proximity, while complex tasks are transferred to the cloud data center for its computation and storage capabilities. However, these approaches have drawbacks in terms of energy consumption and transmission delay, and require task-resource compatibility. This study proposes an MGWO algorithm to address these challenges and the simulation results show its effectiveness in reducing delay and energy consumption compared to existing algorithms.

IEEE ACCESS (2023)

添加到收藏夹

Article Engineering, Electrical & Electronic

TRACTOR: Traffic-aware and power-efficient virtual machine placement in edge-cloud data centers using artificial bee colony optimization

Sayyid Shahab Nabavi et al.

Summary: This study proposes a multi-objective virtual machine placement scheme using an artificial bee colony optimization algorithm for power and network-aware assignment in ECDCs. The scheme aims to minimize network traffic and data center power consumption, and the results show a reduction in energy consumption and network traffic while maintaining other quality of service parameters.

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

An ACO for energy-efficient and traffic-aware virtual machine placement in cloud computing

Huanlai Xing et al.

Summary: This paper introduces a virtual machine placement problem and proposes an energy-and traffic-aware ant colony optimization algorithm to address it. By incorporating three novel schemes, the algorithm demonstrates effective adaptation to the VMP problem and outperforms various state-of-the-art heuristics and metaheuristics in solution quality.

SWARM AND EVOLUTIONARY COMPUTATION (2022)

添加到收藏夹

Article Nanoscience & Nanotechnology

Power aware virtual machine placement in IaaS cloud using discrete firefly algorithm

K. Balaji et al.

Summary: Cloud Computing is a widely adopted computing model that offloads processing workloads to remote servers. The increasing adoption of cloud computing has led to significant power consumption in data centers, which is a major environmental concern. This research proposes a modified discrete firefly algorithm to efficiently schedule virtual machines in order to minimize power consumption. Experimental results demonstrate the superiority of the proposed algorithm compared to Genetic Algorithm and Particle Swarm Optimization in terms of power conservation.

APPLIED NANOSCIENCE (2022)

添加到收藏夹

Article Computer Science, Information Systems

Job scheduling problem in fog-cloud-based environment using reinforced social spider optimization

P. Kuppusamy et al.

Summary: This paper introduces a reinforced strategy Dynamic Opposition Learning based Social Spider Optimization (DOLSSO) algorithm to enhance workflow scheduling in fog computing. The proposed algorithm achieves better CPU utilization and less energy consumption compared to other techniques.

JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS (2022)

添加到收藏夹

Article Computer Science, Hardware & Architecture

Utilization aware and network I/O intensive virtual machine placement policies for cloud data center

Kamalesh Karmakar et al.

Summary: The paper discusses the virtual machine placement problem in high-performance computing in the cloud environment and introduces the concept of virtual clusters to reduce communication costs. Various heuristics and meta-heuristic algorithms based on genetic algorithms are proposed and compared for performance evaluation.

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS (2022)

添加到收藏夹

Article Computer Science, Hardware & Architecture

ARPS: An Autonomic Resource Provisioning and Scheduling Framework for Cloud Platforms

Mohit Kumar et al.

Summary: With the increasing adoption of Cloud computing, the need for multi-objective scheduling algorithms to provide suitable services has become important. This paper introduces the ARPS framework, which has the capability to optimize execution time and cost, and integrates with the SMO algorithm to efficiently allocate Cloud services. Experimental results demonstrate the superiority of the proposed mechanism over existing mechanisms.

IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING (2022)

添加到收藏夹

Review Computer Science, Information Systems

A review on genetic algorithm: past, present, and future

Sourabh Katoch et al.

Summary: This paper discusses recent advances in genetic algorithms, analyzing selected algorithms of interest in the research community. It helps new and demanding researchers gain a broader understanding of genetic algorithms. The review covers well-known algorithms, genetic operators, research domains, and future research directions in genetic algorithms.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

PSO-based novel resource scheduling technique to improve QoS parameters in cloud computing

Mohit Kumar et al.

NEURAL COMPUTING & APPLICATIONS (2020)

添加到收藏夹

Article Computer Science, Information Systems

Green Cloud Computing Using Proactive Virtual Machine Placement: Challenges and Issues

Mohammad Masdari et al.

JOURNAL OF GRID COMPUTING (2020)

添加到收藏夹

Review Computer Science, Information Systems

Bio-inspired virtual machine placement schemes in cloud computing environment: taxonomy, review, and future research directions

Mohammad Masdari et al.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2020)

添加到收藏夹

Editorial Material Multidisciplinary Sciences

Recalibrating global data center energy-use estimates

Eric Masanet et al.

SCIENCE (2020)

添加到收藏夹

Article Computer Science, Information Systems

An energy-efficient algorithm for virtual machine placement optimization in cloud data centers

Sadoon Azizi et al.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2020)

添加到收藏夹

Article Computer Science, Information Systems

Modified Dragonfly Algorithm for Optimal Virtual Machine Placement in Cloud Computing

Atul Tripathi et al.

JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Autonomic cloud resource provisioning and scheduling using meta-heuristic algorithm

Mohit Kumar et al.

NEURAL COMPUTING & APPLICATIONS (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

A crossover operator for improving the efficiency of permutation-based genetic algorithms

Behrooz Koohestani

EXPERT SYSTEMS WITH APPLICATIONS (2020)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Multi-objective temporal bin packing problem: An application in cloud computing

Nursen Aydin et al.

COMPUTERS & OPERATIONS RESEARCH (2020)

添加到收藏夹

Article Computer Science, Hardware & Architecture

Multi-resource balance optimization for virtual machine placement in cloud data centers

Wenting Wei et al.

COMPUTERS & ELECTRICAL ENGINEERING (2020)

添加到收藏夹

Article Computer Science, Information Systems

Multi-Objective Energy Efficient Virtual Machines Allocation at the Cloud Data Center

Neeraj Kumar Sharma et al.

IEEE TRANSACTIONS ON SERVICES COMPUTING (2019)

添加到收藏夹

Article Computer Science, Information Systems

Improved multiobjective salp swarm optimization for virtual machine placement in cloud computing

Shayem Saleh Alresheedi et al.

HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Survey of quality measures for multi-objective optimization: Construction of complementary set of multi-objective quality measures

Maciej Laszczyk et al.

SWARM AND EVOLUTIONARY COMPUTATION (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Optimal VM placement in distributed cloud environment using MOEA/D

Arunkumar Gopu et al.

SOFT COMPUTING (2019)

添加到收藏夹

Proceedings Paper Computer Science, Hardware & Architecture

On Multicast-Oriented Virtual Network Function Placement: A Modified Genetic Algorithm

Xinhan Wang et al.

SIGNAL AND INFORMATION PROCESSING, NETWORKING AND COMPUTERS (ICSINC) (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Reference Point Specification in Inverted Generational Distance for Triangular Linear Pareto Front

Hisao Ishibuchi et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2018)

添加到收藏夹

Article Computer Science, Artificial Intelligence

An Energy Efficient Ant Colony System for Virtual Machine Placement in Cloud Computing

Xiao-Fang Liu et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2018)

添加到收藏夹

Article Computer Science, Theory & Methods

Power-Aware and Performance-Guaranteed Virtual Machine Placement in the Cloud

Hui Zhao et al.

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2018)

添加到收藏夹

Article Computer Science, Artificial Intelligence

An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints

Kalyanmoy Deb et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2014)

添加到收藏夹

Article Computer Science, Hardware & Architecture

A multi-objective ant colony system algorithm for virtual machine placement in cloud computing

Yongqiang Gao et al.

JOURNAL OF COMPUTER AND SYSTEM SCIENCES (2013)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.