Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8975
Title: Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm
Authors: Abdulhamid, Shafi’i Muhammad
Abd Latiff, Muhammad Shafie
Madni, Syed Hamid Hussain
Abdullahi, Mohammed
Keywords: Resource scheduling
cloud computing
Metaheuristics algorithms
Cloud Computing security
League championship algorithm
Dynamic clustering
Task scheduling
Fault tolerance
Cloud scheduling
Issue Date: 4-Jul-2016
Publisher: Neural Computing and Applications
Citation: http://dx.doi.org/10.1007/s00521-016-2448-8
Series/Report no.: 279–293 (2018);
Abstract: In cloud computing, resources are dynamicallyprovisioned and delivered to users in a transparent mannerautomatically on-demand. Task execution failure is nolonger accidental but a common characteristic of cloudcomputing environment. In recent times, a number ofintelligent scheduling techniques have been used toaddress task scheduling issues in cloud without muchattention to fault tolerance. In this research article, weproposed a dynamic clustering league championshipalgorithm (DCLCA) scheduling technique for fault toler-ance awareness to address cloud task execution whichwould reflect on the current available resources andreduce the untimely failure of autonomous tasks. Exper-imental results show that our proposed technique pro-duces remarkable fault reduction in task failure asmeasured in terms of failure rate. It also shows that theDCLCA outperformed the MTCT, MAXMIN, ant colonyoptimization and genetic algorithm-based NSGA-II byproducing lower makespan with improvement of 57.8,53.6, 24.3 and 13.4 % in the first scenario and 60.0, 38.9,31.5 and 31.2 % in the second scenario, respectively.Considering the experimental results, DCLCA providesbetter quality fault tolerance aware scheduling that willhelp to improve the overall performance of the cloudenvironment.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8975
ISSN: 1433-3058
Appears in Collections:Cyber Security Science

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