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WSPML:An Approach for Enhancing Live VM Migration
http://hdl.handle.net/20.500.12678/0000004710
http://hdl.handle.net/20.500.12678/0000004710238fd125-99dc-4aab-946b-89a12c68f896
6dcd3f1d-6990-4d86-8411-8cb90d0027db
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Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | WSPML:An Approach for Enhancing Live VM Migration | |||||
Language | en | |||||
Publication date | 2012-02-28 | |||||
Authors | ||||||
Zaw, Ei Phyu | ||||||
Thein, Ni Lar | ||||||
Description | ||||||
Live VM migration has been a powerful tool tofacilitate system maintenance, load balancing, faulttolerance, and power-saving in data centers. Precopytechnique is the best suited approach for livemigration. Although pre-copy based live migrationprovides minimal service downtime, total migrationtime is prolonged which affect on the degradation ofVM’s performance. VM needs the improvement inperformance of migration process by reducing thetotal migration time. In this paper, working setprediction using machine learning (WSPML) isproposed to reduce the total migration time. It usesthe prediction model with historical data during thelive VM migration process. At first, it trainsexperimental dataset which includes the performanceparameters collected from various workloads bymachine learning techniques to build the bestprediction model and then predict the working setwhich can affect the total migration time. Weevaluated the effectiveness of the working setprediction algorithm with various workloads withsimulation model and the experimental result showsthat WSPML can more reduce the total migrationtime in live VM migration than XEN’s default precopy based live migration. | ||||||
Keywords | ||||||
Virtual Machine, Live VM migration, Pre-copy, Machine Learning Techniques, Total Migration Time | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/415 | |||||
Journal articles | ||||||
Tenth International Conference On Computer Applications (ICCA 2012) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |