scholarly journals Deadline Aware Prioritized Task Scheduling Algorithm in Cloud Computing

2019 ◽  
Vol 8 (2S11) ◽  
pp. 815-818
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Service Providers ◽  
Scheduling Algorithm ◽  
Challenging Issue ◽  
Computing Paradigm ◽  
Task Scheduling Algorithm ◽  
Heuristics Algorithm ◽  
Available Resources

Cloud Computing is a computing Paradigm in which services are provided by service providers on pay-per-use. Task Scheduling is the challenging issue in cloud computing. Task scheduling refers to allocating tasks to available resources to achieve better performance of the system. Here we have proposed a Heuristics algorithm to schedule tasks in given resources which satisfies the QoS of system taking Priority and Deadline of tasks as parameters. Our algorithm is compared with existing algorithms like EDF and TLD algorithms. Our algorithm provides better makespan, increases throughput and utilize resources well compared to existing algorithms

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

scholarly journals Innovative Task Scheduling Algorithm in Cloud Computing

2020 ◽  
Vol 981 ◽  
pp. 022023
Author(s):  
S. Magesh Kumar ◽  
V. Auxilia Osvin Nancy ◽  
A Balasundaram ◽  
Seena Naik korra ◽  
D Kothandaraman ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Scheduling Algorithm
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