Dynamic Resources Configuration for Coevolutionary Scheduling of Scientific Workflows in Cloud Environment

2017 ◽  
pp. 13-23 ◽  
Author(s):  
Alexander A. Visheratin ◽  
Mikhail Melnik ◽  
Denis Nasonov
Keyword(s):  
Scientific Workflows ◽  
Cloud Environment

Multi-objective scheduling strategy for scientific workflows in cloud environment: A Firefly-based approach

2020 ◽  
Vol 93 ◽  
pp. 106411
Author(s):  
Mainak Adhikari ◽  
Tarachand Amgoth ◽  
Satish Narayana Srirama
Keyword(s):  
Scientific Workflows ◽  
Cloud Environment ◽  
Scheduling Strategy ◽  
Multi Objective

Budget-deadline constrained approach for scientific workflows scheduling in a cloud environment

2020 ◽  
Author(s):  
Naqin Zhou ◽  
Weiwei Lin ◽  
Wei Feng ◽  
Fang Shi ◽  
Xiongwen Pang
Keyword(s):  
Scientific Workflows ◽  
Cloud Environment

LPSO: An Algorithm for Scheduling scientific workflows in a Cloud Environment

2015 ◽  
Vol 60 (7A) ◽  
pp. 30-40
Author(s):  
Phan Thanh Toàn ◽  
Nguyễn Thế Lộc ◽  
Nguyễn Doãn Cường
Keyword(s):  
Scientific Workflows ◽  
Cloud Environment

scholarly journals Design of Energy Aware Scheduling Algorithm for Executing Scientific Workflows in Cloud

2019 ◽  
Vol 9 (2) ◽  
pp. 1305-1311
Keyword(s):  
Energy Efficient ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Scientific Workflow ◽  
Scientific Workflows ◽  
Cloud Environment ◽  
Scientific Applications ◽  
Energy Aware ◽  
Efficient Manner ◽  
The Given

The usage of cloud computing and its resources for the execution of scientific workflow is a rapidly increasing demand. The Scientific applications are generally large in scale; even a single scientific workflow includes more number of complex tasks. Execution of these tasks can be made successful only by deploying it in the cloud virtual machines, because only cloud environment can only provide very large number of computing assets. In cloud, every processing resource is given as Virtual Machine. Any scientific workflow deployed in the cloud needs large number of virtual machines so; huge amount of computational energy is spent by the virtual machines to execute multifaceted scientific workflows. Hence there arises the need to utilize the cloud resources in an energy efficient way. Also, if the virtual machines are planned to schedule in an energy efficient manner there is an increase of makepsan of the workflow which is going to be an important parameter for completing the workflow within the deadline. So, the need for executing scientific workflows in energy efficient way with reduced makespan becomes a major issue among the researchers. It also becomes very challenging task to executing a scientific workflow in within the given deadline of a task in the given workflow. To address these issues, a new Energy Aware workflow scheduling algorithm is proposed and designed with improved makespan for the execution of different scientific applications in cloud environment.

Sign in / Sign up

Export Citation Format

Share Document