Executable System-of-Systems architecting based on DoDAF meta-model

Li, Long; Dou, Yajie; Ge, Bingfeng; Yang, Kun; Chen, Yingwu

doi:10.1109/sysose.2012.6384204

Cited by 9 publications

(10 citation statements)

References 7 publications

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“…The use of timed Petri nets is also applicable, allowing delays to be introduced in the model, which would reflect the cyclic transmission cycle of data link messages. Coloured Petri nets have been utilised in the development of executable architecture through an extension to DoDAF (Li et al, 2012), providing a dynamic element to the static models currently produced by DoDAF (and MoDAF).…”

Section: Application To Data Looping Case Studymentioning

confidence: 99%

“…Generally the development of a MODAF model is based on numerous scenarios, however, this implies that component systems are known, as least at a generic level, meaning applicability is limited to directed and acknowledged types of SoS [as defined by ]. In order to add an executable element to DoDAF, the US equivalent to MoDAF, research is being undertaken to add a dynamic view through the use of coloured Petri nets (Li et al, 2012).…”

Section: Enterprise Architecture Frameworkmentioning

confidence: 99%

“…However, they are unsuited to identifying emergent behaviour because of their static nature, although a dynamic element is the subject of current research (Li et al, 2012). At present functions can be identified by EAs, but their behaviour cannot be modelled.…”

Section: Application Strengths Of Ea Frameworkmentioning

confidence: 99%

“…Petri nets are a more specialised modelling technique and their selection will likely depend on the practitioner's experience. However, the use of Petri nets for the creation of executable DoDAF views (Li et al, 2012) represents an important development, which may become an essential SoS modelling approach. The structured nature of DES/DEVS and Petri nets does require a model to implement all component systems and interactions between them.…”

Section: General Comments On the M Ands Toolsmentioning

confidence: 99%

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A model based approach to system of systems risk management

Kinder

Henshaw

Siemieniuch

2015

2015 10th System of Systems Engineering Conference (SoSE)

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The failure of many System of Systems (SoS) enterprises can be attributed to the inappropriate application of traditional Systems Engineering (SE) processes within the SoS domain, because of the mistaken belief that a SoS can be regarded as a single large, or complex, system. SoS Engineering (SoSE) is a sub-discipline of SE; Risk Management and Modelling and Simulation (M&S) are key areas within SoSE, both of which also lie within the traditional SE domain. Risk Management of SoS requires a different approach to that currently taken for individual systems; if risk is managed for each component system then it cannot be assumed that the aggregated affect will be to mitigate risk at the SoS level.A literature review was undertaken examining three themes: (1) SoS Engineering (SoSE), (2) M&S and (3) Risk.Theme 1 of the literature provided insight into the activities comprising SoSE and its difference from traditional SE with risk management identified as a key activity.The second theme discussed the application of M&S to SoS, providing an output, which supported the identification of appropriate techniques and concluding that, the inherent complexity of a SoS required the use of M&S in order to support SoSE activities.Current risk management approaches were reviewed in theme 3 as well as the management of SoS risk. Although some specific examples of the management of SoS risk were found, no mature, general approach was identified, indicating a gap in current knowledge. However, it was noted most of these examples were underpinned by M&S approaches.It was therefore concluded a general approach SoS risk management utilising M&S methods would be of benefit.In order to fill the gap identified in current knowledge, this research proposed a new model based approach to Risk Management where risk identification was supported by a framework, which combined SoS system of interest dimensions with holistic risk types, where the resulting risks and contributing factors are captured in a causal network.Analysis of the causal network using a model technique selection tool, developed as part of this research, allowed the causal network to be simplified through the replacement of groups of elements within the network by appropriate supporting models.The Bayesian Belief Network (BBN) was identified as a suitable method to represent SoS risk.Supporting models run in Monte Carlo Simulations allowed data to be generated from which A Model Based Approach to System of Systems Risk Management iii the risk BBNs could learn, thereby providing a more quantitative approach to SoS risk management. A method was developed which provided context to the BBN risk output through comparison with worst and best-case risk probabilities.The model based approach to Risk Management was applied to two very different case studies: Close Air Support mission planning and the Wheat Supply Chain, UK National Food Security risks, demonstrating its effectiveness and adaptability.The research established that the SoS SoI is essential for effective SoS risk i...

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Section: Application To Data Looping Case Studymentioning

confidence: 99%

Section: Enterprise Architecture Frameworkmentioning

confidence: 99%

Section: Application Strengths Of Ea Frameworkmentioning

confidence: 99%

Section: General Comments On the M Ands Toolsmentioning

confidence: 99%

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A model based approach to system of systems risk management

Kinder

Henshaw

Siemieniuch

2015

2015 10th System of Systems Engineering Conference (SoSE)

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“…Features that DM2 contribute to DoDAF are a constrained vocabulary, specific semantics and format, increased discovery and understandability and finally, widely adopted integration and analysis (DoD Deputy Chief Information Officer, 2009). Several papers cite the ambiguous definition of terms as a significant challenge with development of executable architectures (Ge, Hipel, Li, & Chen, 2012;Li, Dou, Ge, Yang, & Chen, 2012;Wagenhals, Liles, & Levis, 2009). To complete the release of this updated version of the framework, the DoDAF office provided an extensive data dictionary and mapping resource for explicitly defining terms and mapping those terms to sub models and products.…”

Section: Dodaf Backgroundmentioning

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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