Energy-Aware Workflow Scheduling Algorithm for the Deployment of Scientific Workflows in Cloud

2018 ◽  
pp. 153-162
Author(s):  
S. Balamurugan ◽  
S. Saraswathi
Keyword(s):  
Scheduling Algorithm ◽  
Scientific Workflows ◽  
Workflow Scheduling ◽  
Energy Aware

Cost Effective Heuristic workflow scheduling algorithm in Cloud under Deadline Constraint

2019 ◽  
Vol 12 ◽  
Author(s):  
Jasraj Meena ◽  
Manu Vardhan
Keyword(s):  
Cloud Computing ◽  
Scheduling Algorithm ◽  
Cost Effective ◽  
Scientific Workflow ◽  
Scientific Workflows ◽  
Workflow Scheduling ◽  
Performance Variation ◽  
Acquisition Delay ◽  
Very High ◽  
Deadline Constraint

Cloud computing is used to deliver IT resources over the internet. Due to the popularity of cloud computing, nowadays, most of the scientific workflows are shifted towards this environment. There are lots of algorithms has been proposed in the literature to schedule scientific workflows in the cloud, but their execution cost is very high as well as they are not meeting the user-defined deadline constraint. This paper focuses on satisfying the userdefined deadline of a scientific workflow while minimizing the total execution cost. So, to achieve this, we have proposed a Cost-Effective under Deadline (CEuD) constraint workflow scheduling algorithm. The proposed CEuD algorithm considers all the essential features of Cloud and resolves the major issues such as performance variation, and acquisition delay. We have compared the proposed CEuD algorithm with the existing literature algorithms for scientific workflows (i.e., Montage, Epigenomics, and CyberShake) and getting better results for minimizing the overall execution cost of the workflow while satisfying the user-defined deadline.

scholarly journals Bandwidth-Aware Scheduling of Workflow Application on Multiple Grid Sites

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Harshadkumar B. Prajapati ◽  
Vipul A. Shah
Keyword(s):  
Open Source ◽  
Scheduling Algorithm ◽  
Scientific Workflows ◽  
Workflow Scheduling ◽  
Grid Environment ◽  
Data Movement ◽  
Workflow Mapping ◽  
Workflow Application ◽  
Algorithm Level ◽  
Better Than

Bandwidth-aware workflow scheduling is required to improve the performance of a workflow application in a multisite Grid environment, as the data movement cost between two low-bandwidth sites can adversely affect the makespan of the application. Pegasus WMS, an open-source and freely available WMS, cannot fully utilize its workflow mapping capability due to unavailability of integration of any bandwidth monitoring infrastructure in it. This paper develops the integration of Network Weather Service (NWS) in Pegasus WMS to enable the bandwidth-aware mapping of scientific workflows. Our work demonstrates the applicability of the integration of NWS by making existing Heft site-selector of Pegasus WMS bandwidth aware. Furthermore, this paper proposes and implements a new workflow scheduling algorithm—Level based Highest Input and Processing Weight First. The results of the performed experiments indicate that the bandwidth-aware workflow scheduling algorithms perform better than bandwidth-unaware algorithms: Random and Heft of Pegasus WMS. Moreover, our proposed workflow scheduling algorithm performs better than the bandwidth-aware Heft algorithms. Thus, the proposed bandwidth-aware workflow scheduling enhances capability of Pegasus WMS and can increase performance of workflow applications.

Cost and Energy Aware Scheduling Algorithm for Scientific Workflows with Deadline Constraint in Clouds

2018 ◽  
Vol 11 (4) ◽  
pp. 713-726 ◽  
Author(s):  
Zhongjin Li ◽  
Jidong Ge ◽  
Haiyang Hu ◽  
Wei Song ◽  
Hao Hu ◽  
...  
Keyword(s):  
Scheduling Algorithm ◽  
Scientific Workflows ◽  
Energy Aware ◽  
Energy Aware Scheduling ◽  
Deadline Constraint

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.

Workflow scheduling algorithm based on load balance in grid

2011 ◽  
Vol 30 (12) ◽  
pp. 3184-3186
Author(s):  
Ming-quan WANG ◽  
Jiong YU ◽  
Yuan TIAN ◽  
Yun HAN
Keyword(s):  
Load Balance ◽  
Scheduling Algorithm ◽  
Workflow Scheduling
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