Efficient online detection of temporal patterns

Shlomi Dolev; Jonathan Goldfeld; Rami Puzis; K. Muni Venkateswarlu

doi:10.7717/peerj-cs.53

Efficient online detection of temporal patterns

Shlomi Dolev
, Jonathan Goldfeld
, Rami Puzis
, K. Muni Venkateswarlu

Research output: Contribution to journal › Article › peer-review

Abstract

Identifying a temporal pattern of events is a fundamental task of online (real- time) verification. We present efficient schemes for online monitoring of events for identifying desired/undesired patterns of events. The schemes use preprocessing to ensure that the number of comparisons during run-time is minimized. In particular, the first comparison following the time point when an execution sub-sequence cannot be further extended to satisfy the temporal requirements halts the process that monitors the sub-sequence.

Original language	American English
Article number	e53
Journal	PeerJ Computer Science
Volume	2016
Issue number	4
DOIs	https://doi.org/10.7717/peerj-cs.53
State	Published - 1 Jan 2016

Keywords

Pattern matching
Time series
Verification

ASJC Scopus subject areas

General Computer Science

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10.7717/peerj-cs.53

Cite this

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title = "Efficient online detection of temporal patterns",

abstract = "Identifying a temporal pattern of events is a fundamental task of online (real- time) verification. We present efficient schemes for online monitoring of events for identifying desired/undesired patterns of events. The schemes use preprocessing to ensure that the number of comparisons during run-time is minimized. In particular, the first comparison following the time point when an execution sub-sequence cannot be further extended to satisfy the temporal requirements halts the process that monitors the sub-sequence.",

keywords = "Pattern matching, Time series, Verification",

author = "Shlomi Dolev and Jonathan Goldfeld and Rami Puzis and \{Muni Venkateswarlu\}, K.",

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AU - Puzis, Rami

AU - Muni Venkateswarlu, K.

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Y1 - 2016/1/1

N2 - Identifying a temporal pattern of events is a fundamental task of online (real- time) verification. We present efficient schemes for online monitoring of events for identifying desired/undesired patterns of events. The schemes use preprocessing to ensure that the number of comparisons during run-time is minimized. In particular, the first comparison following the time point when an execution sub-sequence cannot be further extended to satisfy the temporal requirements halts the process that monitors the sub-sequence.

AB - Identifying a temporal pattern of events is a fundamental task of online (real- time) verification. We present efficient schemes for online monitoring of events for identifying desired/undesired patterns of events. The schemes use preprocessing to ensure that the number of comparisons during run-time is minimized. In particular, the first comparison following the time point when an execution sub-sequence cannot be further extended to satisfy the temporal requirements halts the process that monitors the sub-sequence.

KW - Pattern matching

KW - Time series

KW - Verification

UR - https://www.scopus.com/pages/publications/85030085480

U2 - 10.7717/peerj-cs.53

DO - 10.7717/peerj-cs.53

M3 - Article

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VL - 2016

JO - PeerJ Computer Science

JF - PeerJ Computer Science

IS - 4

M1 - e53

ER -

Efficient online detection of temporal patterns

Abstract

Keywords

ASJC Scopus subject areas

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