An improvised grid resource allocation and classfication through regression
prediction; Regression; Resource monitoring
The resource allocation is one of the important mechanisms of grid computing, which helps to assign the available resources very efficiently. The one of the issue of grid computing is fixing the target nodes during the grid job execution. In existing method, resource monitored data are collected from grid then jobs are allocated to the resources based on available data, through regression algorithm. In this method total execution time of an application and run time of jobs should be high. The proposed method mitigate running time by classify the resources in the data collected from grid based on dwell time using novel classification algorithm. It reduces the jobs run time and fit the best available resources to the jobs in the computational grid. 2017 IEEE.
Krishnakumar A.; Kumaran T.S.; Balamurugan M.
2017 Conference on Emerging Devices and Smart Systems, ICEDSS 2017, pp. 129-132.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICEDSS.2017.8073672 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039908223&doi=10.1109%2fICEDSS.2017.8073672&partnerID=40&md5=555d1467932b2db43559537b45db0ece
Krishnakumar A., Dept of CSE, ACS College of Engineering, India; Kumaran T.S., Dept of CSE, ACS College of Engineering, India; Balamurugan M., Dept of CSE, Christ Unitversity, Faculty of Engineering, India