TY - JOUR

T1 - Temporal Models on Time Series Databases

AU - Mazak-Huemer, Alexandra

AU - Wolny, Sabine

AU - Gomez, Abel

AU - Cabot, Jordi

AU - Wimmer, Manuel

AU - Kappel, Gerti

N1 - doi: 10.5381/jot

PY - 2020

Y1 - 2020

N2 - With the emergence of Cyber-Physical Systems (CPS), more and more sophisticated runtime monitoring solutions have been proposed in order to deal with extensive execution logs. One promising development in this respect is the integration of time series databases which allow to store massive amounts of historical data as well as to provide fast query capabilities to reason about runtime properties of CPS.In this paper, we discuss how conceptual modeling can benefit from time series databases and vice versa. In particular, we present how metamodels and their instances, i.e., models, can be partially mapped to time series databases. Thus, the traceability between design and simulation/runtime activities can be ensured by retrieving and accessing runtime information, i.e., time series data, in design models. On this basis, the contribution of this paper is three-fold. First, a dedicated profile for annotating design models for time series databases is presented. Second, a mapping for integrating the metamodeling framework EMF with InfluxDB is introduced as a technology backbone enabling two distinct mapping strategies for model information. Third, we demonstrate how continuous time series queries can be combined with the Object Constraint Language (OCL) fornavigation through models, now enriched with derived runtime properties. Finally, we also present an initial evaluation of the different mapping strategies with respect to data storage and query performance. Our initial results show the efficiency of applying derived runtime properties as time series queries also for large model histories.

AB - With the emergence of Cyber-Physical Systems (CPS), more and more sophisticated runtime monitoring solutions have been proposed in order to deal with extensive execution logs. One promising development in this respect is the integration of time series databases which allow to store massive amounts of historical data as well as to provide fast query capabilities to reason about runtime properties of CPS.In this paper, we discuss how conceptual modeling can benefit from time series databases and vice versa. In particular, we present how metamodels and their instances, i.e., models, can be partially mapped to time series databases. Thus, the traceability between design and simulation/runtime activities can be ensured by retrieving and accessing runtime information, i.e., time series data, in design models. On this basis, the contribution of this paper is three-fold. First, a dedicated profile for annotating design models for time series databases is presented. Second, a mapping for integrating the metamodeling framework EMF with InfluxDB is introduced as a technology backbone enabling two distinct mapping strategies for model information. Third, we demonstrate how continuous time series queries can be combined with the Object Constraint Language (OCL) fornavigation through models, now enriched with derived runtime properties. Finally, we also present an initial evaluation of the different mapping strategies with respect to data storage and query performance. Our initial results show the efficiency of applying derived runtime properties as time series queries also for large model histories.

KW - Runtime Models

KW - Query Languages

KW - Model-based Analysis

KW - Temporal Modeling

KW - Time Series Databases

U2 - 10.5381/jot

DO - 10.5381/jot

M3 - Article

VL - 19.2020

SP - 1

EP - 15

JO - Journal of object technology : JOT

JF - Journal of object technology : JOT

SN - 1660-1769

IS - 3

ER -