1. Use of ML and DM Algorithms for Data Storage Management Włodzimierz Funika, Pawel Gielmuda KUKDM’15, Zakopane

2. Motivation and Scope Problems with effective handling and distributed file systems performance Optimization of storage usage, user location handling Optimization of performance of distributed storage system (DSS) Comparison of suitability of machine learning and data mining algorithms for DSS Our approach: Data gathering and processing: Build monitoring tools for GlusterFS and FSS Monitor application records all I/O operations Exported data can be analyzed in WEKA and AQ21 Test sessions performed to gather file system usage (all I/O operations were recorded) Total more than 35k records gathered and analyzed using algorithms: AQ, C4.5, kNN, k-means Suggestions on decisions to improve file system performance

3. Poster no 15