A Study on the Effect of Application and Resource Characteristics on the QoS in Service Provisioning Environments
Author:
Affiliation:
1. National Technical University of Athens, Greece
2. Italian National Research Council, Italy
3. University of the Aegean, Greece
Abstract
Publisher
IGI Global
Subject
Computer Networks and Communications,Hardware and Architecture
Reference27 articles.
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2. Bradford, J. P., & Fortes, J. (1998). Performance and memory access characterization of data mining applications. WWC: Proceedings of the Workload Characterization: Methodology and Case Studies (p. 49). Washington, DC: IEEE Computer Society.
3. Chen, Y., Iyer, S., Liu, X., Milojicic, D., & Sahai, A. (2007). SLA Decomposition: Translating Service Level Objectives to System Level Thresholds. International Conference on Autonomic Computing: Proceedings of the Fourth International Conference on Autonomic Computing (p. 3). Washington, DC: IEEE Computer Society.
4. COPE. Corporate-Scale Resources Context-Sensitive Performance Modeling, EPSRC Project GR/L59610/01.
5. Czezowski, A., & Christen, P. (2002). Performance Analysis of KDD Applications using Hardware Event Counters. Retrieved May 15, 2009, from http://datamining.anu.edu.au/talks/2002/cap2002-kdd.ps.gz
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