Delay-Aware Associate Tasks Scheduling in the Cloud Computing

2015 ◽  
Author(s):  
Mao Yingchi ◽  
Xu Ziyang ◽  
Ping Ping ◽  
Wang Longbao
Keyword(s):  
Cloud Computing ◽  
Tasks Scheduling

DT-MG: many-to-one matching game for tasks scheduling towards resources optimization in cloud computing

2018 ◽  
pp. 1-13 ◽  
Author(s):  
Yassir Samadi ◽  
Mostapha Zbakh ◽  
Claude Tadonki
Keyword(s):  
Cloud Computing ◽  
Tasks Scheduling ◽  
Matching Game

Independent Tasks Scheduling Based on Genetic Algorithm in Cloud Computing

2009 ◽  
Author(s):  
Chenhong Zhao ◽  
Shanshan Zhang ◽  
Qingfeng Liu ◽  
Jian Xie ◽  
Jicheng Hu
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Tasks Scheduling ◽  
Independent Tasks

Task Scheduling of Cloud Computing in Weapon Network System

2014 ◽  
Vol 610 ◽  
pp. 695-698
Author(s):  
Qian Tao ◽  
Bo Pan ◽  
Wen Quan Cui
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Evaluation System ◽  
Large Scale ◽  
Rapid Development ◽  
It Industry ◽  
Control Scheme ◽  
Tasks Scheduling ◽  
Constant Bandwidth

In recent years, the rapid development of cloud computing brings significant innovation in the whole IT industry. For the local tasks scheduling on each computational node of the top model of weapon network, an open task scheduling framework was introduced a task accept control scheme based on the tasks based on load balancing, quality of service (QoS) and an improved constant bandwidth server algorithm was presented. The result of simulation shows that the scheduling policies can improve the schedule speed when the number of tasks increases and can meet the demand better for the real time requirementsof the tactical training evaluation system for complexity and Large-scale.

scholarly journals Tasks Scheduling in Cloud Computing Environment using Workflowsim

2016 ◽  
Vol 8 (3) ◽  
pp. 98-104
Author(s):  
Pradeep Singh Rawat ◽  
Priti Dimri ◽  
G.P. Saroha
Keyword(s):  
Cloud Computing ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Tasks Scheduling

scholarly journals Ganging of Resources via Fuzzy Manhattan Distance Similarity with Priority Tasks Scheduling in Cloud Computing

2018 ◽  
Vol 1 ◽  
pp. 32-41
Author(s):  
S. Sharon Priya ◽  
K. M. Mehata ◽  
W. Aisha Banu
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Manhattan Distance ◽  
Priority Task ◽  
Tasks Scheduling ◽  
Efficient Resource ◽  
Current Task ◽  
Computing Environments ◽  
Resource Characteristics ◽  
The Cost

This paper proposes a fuzzy Manhattan distance-based similarity for gang formation of resources (FMDSGR) method with priority task scheduling in cloud computing. The proposed work decides which processor is to execute the current task in order to achieve efficient resource utilization and effective task scheduling. FMDSGR groups the resources into gangs which rely upon the similarity of resource characteristics in order to use the resources effectively. Then, the tasks are scheduled based on the priority in the gang of processors using gang-based priority scheduling (GPS). This reduces mainly the cost of deciding which processor is to execute the current task. Performance has been evaluated in terms of makespan, scheduling length ratio, speedup, efficiency and load balancing. CloudSim simulator is the toolkit used for simulation and for demonstrating experimental results in cloud computing environments.

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