Towards effective generation of synthetic memory references via markovian models

Alfredo Cuzzocrea, Enzo Mumolo, Marwan Hassani, Giorgio Mario Grasso

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaten (Scopus)

Samenvatting

In this paper we introduce a technique for the synthetic generation of memory references which behave as those generated by given running programs. Our approach is based on a novel Machine Learning algorithm we called Hierarchical Hidden/non Hidden Markov Model (HHnHMM). Short chunks of memory references from a running program are classified as Sequential, Periodic, Random, Jump or Other. Such execution classes are used to train an HHnHMM for that program. Trained HHnHMM are used as stochastic generators of memory reference addresses. In this way we can generate in real time memory reference streams of any length, which mimic the behavior of given programs without the need to store anything.

Originele taal-2Engels
TitelProceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018
RedacteurenClaudio Demartini, Sorel Reisman, Ling Liu, Edmundo Tovar, Hiroki Takakura, Ji-Jiang Yang, Chung-Horng Lung, Sheikh Iqbal Ahamed, Kamrul Hasan, Thomas Conte, Motonori Nakamura, Zhiyong Zhang, Toyokazu Akiyama, William Claycomb, Stelvio Cimato
Plaats van productiePiscataway
UitgeverijIEEE Computer Society
Pagina's199-203
Aantal pagina's5
ISBN van elektronische versie9781538626665
DOI's
StatusGepubliceerd - 8 jun. 2018
Evenement42nd IEEE Computer Software and Applications Conference, (COMPSAC 2018) - Tokyo, Japan
Duur: 23 jul. 201827 jul. 2018
https://www.cloudendure.com/events/compsac-2018-42nd-ieee-computer-society-international-conference-on-computers-software-applications/

Congres

Congres42nd IEEE Computer Software and Applications Conference, (COMPSAC 2018)
Verkorte titelCOMPSAC2018
Land/RegioJapan
StadTokyo
Periode23/07/1827/07/18
Internet adres

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