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TITLE:
Flexible and Realistic Client-centric Evaluation of Personal Clouds via User Stereotypes - TFM:156
Handle: https://hdl.handle.net/20.500.11797/TFM156

Student:Chenglong Zou
Language:Anglès
Title in original language:Flexible and Realistic Client-centric Evaluation of Personal Clouds via User Stereotypes
Title in different languages:Flexible and Realistic Client-centric Evaluation of Personal Clouds via User Stereotypes
Keywords:Personal Cloud Storage, Performance Analysis, Workload Generator
Subject:Enginyeria
Abstract:Abstract The performance evaluation of Personal Clouds (e.g., Dropbox, Google Drive, Box) is challenging due to their fat-client architecture and the absence of realistic workload generators that reproduce the disparate types of user behavior. In this work, we propose a novel storage benchmarking methodology in which the workload is generated by emulating groups of users that exhibit a similar behavior, namely, user stereotypes. Weinstantiate this methodology in BenchBox, a distributed performance analysis tool that integrates: (i) A practical yet accurate model that locally reproduces the aspects of user behavior that matter to the performance of desktop clients (e.g., types of activity, data contents); (ii) A centralized management and real-time monitoring system of Personal Cloud desktop clients. (iii) BenchBox also uses compact files to represent user stereotypes, enabling researchers to share only the behavior of users withoutdisclosing private traces. We show the benefits of BenchBox by exercising public and private Personal Clouds. We show how distinct types of users impact on the performance and efficiency of these systems, which may guide their optimization. Keywords: Personal Cloud Storage, Performance Analysis, Workload Generator, Stereotype.
Project director:Garcia-Tenido, Raúl
Work's codirector:García López, Pedro
Department:Enginyeria Informàtica i Matemàtiques
Education area(s):Enginyeria Informàtica, Seguretat Informàtica i Sistemes Intel·ligents
Entity:Universitat Rovira i Virgili (URV)
TFM credits:12
Work's public defense date:2016-11-15
Academic year:2015-2016
Confidenciality:No
Subject areas:Computer engineering
Creation date in repository:2016-02-09
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