A Model-Driven Approach for Evaluating System of Systems

Xia, Xiaokai; Wu, Ji; Liu, Chao; Xu, Luo

doi:10.1109/iceccs.2013.18

Cited by 13 publications

(15 citation statements)

References 8 publications

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“…Table I shows a comparison among approaches related to ASAS. Approaches highlighted in bold font are model- Table I: Comparison among related approaches Approach 1 2 3 Bi-graph Approach [17] Cavalcante et al [2] DEVS [20] Falkner et al [4] Xia et al [19] ASAS based approaches, i.e., they use abstract models representing the software system and make one or more model transformations for generating a target model. The bi-graph approach offers a mathematical solution for representing and simulating emergent behaviors in SoS [17].…”

Section: Introductionmentioning

confidence: 99%

ASAS: An Approach to Support Simulation of Smart Systems

Neto¹,

Garcés²,

Guessi³

et al. 2018

Proceedings of the Annual Hawaii International Conference on System Sciences

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Smart systems, such as smart cities, smart buildings, and autonomous cars, have recently gained increasing popularity. Each such system is essentially a System-of-Systems (SoS). SoS are dynamically established as alliances among independent and heterogeneous software systems to offer complex functionalities as a result of constituents interoperability. An SoS often supports critical application domains, and, as such, must be reliable. Many SoS have been specified and evaluated for their correct operation using static models. However, specification languages have not supported to capture their inherent dynamic nature nor enabled to monitor their operation. The main contribution of this paper is to present ASAS, an approach to Automatically generate Simulation models for smArt Systems (ASAS) in order to support evaluation of their operation. In particular, our approach makes it possible to transform formal models of the SoS architecture (expressed in SoSADL) into simulation models (expressed in DEVS). We evaluated our approach by conducting two case studies using a flood monitoring system that is intended to be part of a smart city. Results indicate that ASAS can successfully generate functional simulations for the SoS operation, which in turn can enable to reason and monitor an SoS operation, taking into account its dynamic nature.

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Section: Introductionmentioning

confidence: 99%

ASAS: An Approach to Support Simulation of Smart Systems

Neto¹,

Garcés²,

Guessi³

et al. 2018

Proceedings of the Annual Hawaii International Conference on System Sciences

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show abstract

“…The author of this thesis was unable to find any formal architecture software using CPN for simulation. Several papers suggested use of CPNs for simulation via software such as CPN Tools, but alas that software package is not intended to be a systems architecting software and thus not considered as a practical implementation for executable architectures (Janczura, 2009;Jensen et al, 2007;Staines, 2008;Xia et al, 2013).…”

Section: Colored Petri Netsmentioning

confidence: 99%

“…Formal notation and simulation of executable architectures though Colored Petri Nets (CPNs) is an area of active research and is the preferred formalism for many authors proposing executable architecture methods (Ge, Hipel, Yang, & Chen, 2014;Xia, Wu, Liu, & Xu, 2013). CPNs are an extension of standard Petri Nets where the tokens contain information rather than the binary token nature of standard Petri Nets.…”

Section: Colored Petri Netsmentioning

confidence: 99%

Application of Executable Architectures in Early Concept Evaluation

Popisal¹

2015

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This research explores use of executable architectures to guide design decisions in the early stages of system development. Decisions made early in the system development cycle determine a majority of the total lifecycle costs as well as establish a baseline for long term system performance and thus it is vital to program success to choose favorable design alternatives. The development of a representative architecture followed the Architecture Based Evaluation Process as it provides a logical and systematic order of events to produce an architecture sufficient to document and model operational performance. In order to demonstrate the value in the application of executable architectures for trade space decisions, three variants of a fictional unmanned aerial system were developed and simulated. Four measures of effectiveness (MOEs) were selected for evaluation. Two parameters of interest were varied at two levels during simulation to create four test case scenarios against which to evaluate each variant.Analysis of the resulting simulation demonstrated the ability to obtain a statistically significant difference in MOE performance for 10 out of 16 possible test case-MOE combinations. Additionally, for the given scenarios, the research demonstrated the ability to make a conclusive selection of the superior variant for additional development.

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“…Recent studies have investigated the adoption of simulation in software engineering [63], and simulation has certainly been applied for SoS development [16,36,64]. Additionally, initiatives have invested in the simulation of software architectures, but not specifically for software architectures of SoS, such as SySML [65], MatLab/Simulink [66], Palladio 22 [67], Bogado et al [36], and Alexander et al [68].…”

Section: Related Workmentioning

confidence: 99%

Stimuli-SoS: a model-based approach to derive stimuli generators for simulations of systems-of-systems software architectures

et al. 2017

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Background: Systems-of-systems (SoS) are alliances of independent and interoperable software-intensive systems. SoS often support critical domains, being required to exhibit a reliable operation, specially because people's safety relies on their services. In this direction, simulations enable the validation of different operational scenarios in a controlled environment, allowing a benchmarking of its response as well as revealing possible breaches that could lead to failures. However, simulations are traditionally manual, demanding a high level of human intervention, being costly and error-prone. A stimuli generator could aid in by continuously providing data to trigger a SoS simulation and maintaining its operation. Methods: We established a model-based approach termed Stimuli-SoS to support the creation of stimuli generators to be used in SoS simulations. Stimuli-SoS uses software architecture descriptions for automating the creation of such generators. Specifically, this approach transforms SoSADL, a formal architectural description language for SoS, into dynamic models expressed in DEVS, a simulation formalism. We carried out a case study in which Stimuli-SoS was used to automatically produce stimuli generators for a simulation of a flood monitoring SoS. Results:We run simulations of a SoS architectural configuration with 69 constituent systems, i.e., 42 sensors, 9 crowdsourcing systems, and 18 drones. Stimuli generators were automatically generated for each type of constituent. These stimuli generators were capable of receiving the input data from the database and generating the expected stimuli for the constituents, allowing to simulate constituent systems interoperations into the flood monitoring SoS. Using Stimuli-SoS, we simulated 38 days of flood monitoring in little more than 6 h. Stimuli generators correctly forwarded data to the simulation, which was able to reproduce 29 flood alerts triggered by the SoS during a flooding event. In particular, Stimuli-SoS is almost 65 times more productive than a manual approach to producing data for the same type of simulation. Conclusions: Our approach succeeded in automatically deriving a functional stimuli generator that can reproduce environmental conditions for simulating a SoS. In particular, we presented new contributions regarding productivity and automation for the use of a model-based approach in SoS engineering.

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A Model-Driven Approach for Evaluating System of Systems

Cited by 13 publications

References 8 publications

ASAS: An Approach to Support Simulation of Smart Systems

ASAS: An Approach to Support Simulation of Smart Systems

Application of Executable Architectures in Early Concept Evaluation

Stimuli-SoS: a model-based approach to derive stimuli generators for simulations of systems-of-systems software architectures

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