Budget-Deadline Constrained Workflow Scheduling for Heterogeneous Resources

2017 ◽  
Author(s):  
Naqin Zhou ◽  
Deyu Qi ◽  
Wei Feng ◽  
Xinyang Wang ◽  
Yang Shen
Keyword(s):  
Workflow Scheduling ◽  
Heterogeneous Resources

Load and Cost Aware Min-Min Workflow Scheduling Algorithm for Heterogeneous Resources in Fog, Cloud and Edge Scenarios

2022 ◽  
Vol 12 (1) ◽  
pp. 0-0
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Load Balancing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Workflow Scheduling ◽  
Heterogeneous Environment ◽  
Cloud Servers ◽  
Heterogeneous Resources

Fog computing and Edge computing are few of the latest technologies which are offered as solution to challenges faced in Cloud Computing. Instead of offloading of all the tasks to centralized cloud servers, some of the tasks can be scheduled at intermediate Fog servers or Edge devices. Though this solves most of the problems faced in cloud but also encounter other traditional problems due to resource-related constraints like load balancing, scheduling, etc. In order to address task scheduling and load balancing in Cloud-fog-edge collaboration among servers, we have proposed an improved version of min-min algorithm for workflow scheduling which considers cost, makespan, energy and load balancing in heterogeneous environment. This algorithm is implemented and tested in different offloading scenarios- Cloud only, Fog only, Cloud-fog and Cloud-Fog-Edge collaboration. This approach performed better and the result gives minimum makespan, less energy consumption along with load balancing and marginally less cost when compared to min-min and ELBMM algorithms

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Bottom Level Based Heuristic for Workflow Scheduling in Grids

2009 ◽  
Vol 31 (2) ◽  
pp. 282-290 ◽  
Author(s):  
Ying-Chun YUAN ◽  
Xiao-Ping LI ◽  
Qian WANG ◽  
Yi ZHANG
Keyword(s):  
Workflow Scheduling ◽  
Bottom Level

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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