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Identifier uch.csd.msc//1995labrinidis
Title Μέθοδοι Ταξινόμησης Δοσοληψιών σε Ομάδες με Παρόμοια Χαρακτηριστικά Φόρτου Εργασίας
Alternative Title Methods to cluster transactions into utilization classes with similar workload characteristics
Creator Labrinidis, Alexandros
Contributor Χ. Νικολάου
Abstract Knowledge of the workload intrinsic characteristics is essential for dynamic goal oriented workload control algorithms used to optimize the distributed online transaction processing (OLTP) system's performance behavior, for example through the use of transaction routing algorithms. ``Intrinsic characteristics'' are not dependent on arrival rates, and they include the average number of database accesses, the files accessed, the CPU demand and the average number of synchronization points. CLUE is an environment for clustering transactions according to their workload intrinsic characteristics. It uses execution traces from distributed OLTP systems in order to cluster transactions with high data affinity in utilization classes. HALC is a simple, fast, heuristic algorithm that was developed to cope with the large volume of trace data. A Test Suite Generator was developed in order to create synthetic trace files as input to CLUE. Validation of CLUE's correctness has been made through the use of synthetic trace files. HALC's speed and quality of clustering were evaluated in comparison with the ISODATA and Bond Energy algorithms on real traces. Results have shown that HALC is exceptionally fast and that the quality of the clustering is always really good.
Subject Distributed Online Transaction Processing (OLTP), Clustering algorithm, Workload Characterization, Data Affinity
α) Παράλληλα και Κατανεμημένα Συστήματα, β) Αρχιτεκτονική Υπολογιστών και Ψηφιακά Συστήματα
Issue date 1995-11-01
Date available 1997-06-2
Collection   School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
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