- #YOUTUBE MODELIO SYSML HOW TO#
- #YOUTUBE MODELIO SYSML DRIVER#
- #YOUTUBE MODELIO SYSML SOFTWARE#
- #YOUTUBE MODELIO SYSML SERIES#
Unreliable: no transaction policy, crash holding locks or state,. Inconsistent: siloed app states, checkpoints & versions. Hyper-scale value with simplicity of one: controller, policy, protocol,Īll data should be in data plane including metadata (transactions, (SDN)¹ to control & program any resource, any where, any time. #YOUTUBE MODELIO SYSML SOFTWARE#
PushingHWstate to data layer is identical.ĭata middleware handles all Semantics and Quality with future proof lifecycle, greatlysimplifyingSW& HW.Īll control should be in control plane, like Software Defined Network All control can be remote, including repurposingall SW and all HW that has SW-Semantics (SDN, SD-IOT)Ģ. IoT Data Control = Stateless SW & HW Layers, exposed for controlġ. The term “Quality” will refer to ‘Security, FuSa and QoS (including Fault Tolerance and all 23 ITIL flows)”
#YOUTUBE MODELIO SYSML HOW TO#
Our Part1 focus is How to Develop “composable: Semantics, Security, FuSa and QoS” and Part2 How to Validate it. Formal ontologies, holistic gluefor meaning analysis and solutions.ġ.
Semantic¹ Models: domain-specific(retail, industrial, etc.) and physical-specific (time, space,. Metadata: standard annotations for M2M integration, processing, query andreasoning. Otherwise digital twin does not map to physical or otherĭigital twins, and severely limits analyticsand autonomic (self*). #YOUTUBE MODELIO SYSML SERIES#
Data: Fused sensor data needs identity, geospatial and time series data to know “which ThingsĬan do what for where and when”. 
Security¹ adds OT inner network and actuation, to IT surface area.ĭata drives driverless,factories,retail,home,etc. Controlled actuation needsFunctional Safety (FuSa¹) and Quality of Service (QoS¹). Technology, not IT), connected by Internet (brieflyTCP/IP, DNS) IoT = OT control network of machine actionable dataĬontrolledsystems of systems (SoS) of sensor and actuators (so Operations *Other names and brands may be claimedas the property of others Call to Action: Data Drives, Formal Develop Data, Data Graph Drivenīackup: Tips & labs to quickly learn SysML for IOT. Part2: validating above, Autonomous Agents. #YOUTUBE MODELIO SYSML DRIVER#
What Limits Data (from being the only driver and first class citizen)?.Data Graph Driven replacements (for internet, computers, AI & human contracts) ß.E2E Canonical SysML: Inputs, Ports and Outputs ß long term MBSE hub.Formal MBSE Dev = OOAD process + SysML language + tool ß long term how.Intro: What is IoT? IoT Maturity Levels? How is IoT Development Different?.
IoT = OT control network of machine actionable data ß short term what. For the purpose of evaluation, we apply our proposed logical framework to select an exemplary MBSE tool for interdisciplinary application.Develop Future Proof IoT: Composable Semantics, Security, FuSa, and QoS Through this process, a well-defined functional structure of MBSE tools is sketched, and in order to identify the properties of an ideal tool, all the attributes of different MBSE tools are mapped to a common platform. Subsequently each tool performance is assessed using a decision matrix. QFD is performed to analyze the user needs with respect to evaluable technical properties. To compare the performance of the considered tools, a set of user needs is defined. Market research and extensive discussions with MBSE tool vendors and academia show the current situation of MBSE tools. As customers are at the center of any product, accordingly the needs of MBSE tool users are addressed within this research as the fundamental starting point. For this purpose, we propose a logical framework for MBSE tool selection, which is based on market research, the approaches of Quality Function Deployment (QFD), and decision matrix. 
This paper tries to serve as a guideline to find the ideal tool for a specific industrial application as well as to highlight the key criteria that an industry might consider. However, the variety and complexity of MBSE tools pose difficulties in particular industrial applications.
Model-Based Systems Engineering (MBSE) has emerged with great potential to fulfill the non-linearly rising demand in interdisciplinary engineering, e.g., product development.
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