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Rewriting Large Multimedia Application Execution Traces with few Event Sequences

Title: Rewriting Large Multimedia Application Execution Traces with few Event Sequences
Authors: Kamdem Kengne, Christiane; Fopa, Leon Constantin; Termier, Alexandre; Ibrahim, Noha; Rousset, Marie-Christine; Washio, Takashi; Santana, Miguel
Contributors: Laboratoire d'Informatique de Grenoble (LIG); Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS); Heterogeneous and Adaptive distributed DAta management Systems (HADAS); Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS); Institute of Scientific and Industrial Research; The University of Osaka (UOsaka); STMicroelectronics Crolles (ST-CROLLES); Inderjit S. Dhillon
Source: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) ; KDD 2013 - International Conference on Knowledge Discovery and Data Mining ; https://hal.science/hal-00923538 ; KDD 2013 - International Conference on Knowledge Discovery and Data Mining, Aug 2013, Chicago, IL, United States. pp.1348-1356, ⟨10.1145/2487575.2488211⟩
Publisher Information: CCSD; ACM
Publication Year: 2013
Collection: Université Grenoble Alpes: HAL
Subject Terms: H.3.1 Content Analysis and Indexing Subjects: Abstracting methods; H.2.8 Database applications Subjects: Data mining; [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]
Subject Geographic: Chicago; IL; United States
Description: Session Industrial and government emerging (Security & Privacy) ; International audience ; The analysis of multimedia application traces can reveal important information to enhance program execution comprehension. However typical size of traces can be in gigabytes, which hinders their effective exploitation by application developers. In this paper, we study the problem of finding a set of sequences of events that allows a reduced-size rewriting of the original trace. These sequences of events, that we call blocks, can simplify the exploration of large execution traces by allowing application developers to see an abstraction instead of low-level events. The problem of computing such set of blocks is NP-hard and naive approaches lead to prohibitive running times that prevent analysing real world traces. We propose a novel algorithm that directly mines the set of blocks. Our experiments show that our algorithm can analyse real traces of up to two hours of video. We also show experimentally the quality of the set of blocks proposed, and the interest of the rewriting to understand actual trace data.
Document Type: conference object
Language: English
DOI: 10.1145/2487575.2488211
Availability: https://hal.science/hal-00923538; https://doi.org/10.1145/2487575.2488211
Accession Number: edsbas.4DF91D10
Database: BASE