.png){kind=icon}
返回
Efficient dynamic resource allocation method for cloud computing environment
.png){kind=icon}
PRE
AI
DOI：10.1007/s10586-020-03053-x.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The dynamic resource allocation is a good feature of the cloud computing environment. However, it faces serious problems in terms of service quality, fault tolerance, and energy consumption. It was necessary, then, to find an effective method that can effectively address these important issues and increase cloud performance. This paper presents a dynamic resource allocation model that can meet customer demand for resources with improved and faster responsiveness. It also proposes a multi-objective search algorithm called Spacing Multi-Objective Antlion algorithm (S-MOAL) to minimize both the makespan and the cost of using virtual machines. In addition, its impact on fault tolerance and energy consumption was studied. The simulation revealed that our method performed better than the PBACO, DCLCA, DSOS and MOGA algorithms, especially in terms of makespan.
Keyword:
Cloud computing
Dynamic resource allocation
Makespan
Cost
Task scheduling
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.1
论文数:
5.0K
被引数:
7.5K
机构
引用论文
Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems多目标蚁狮优化器: 一种求解工程问题的多目标优化算法.png)
APPLIED INTELLIGENCE
APPLIED INTELLIGENCEIF3.5
PREAI
分享收藏Dynamic energy-aware scheduling for parallel task-based application in cloud computing云计算中基于并行任务的动态能量感知调度
OAAI
OAAI分享收藏
查看更多内容