A Simulation-Based System Design Toolfor Avionic Fiber-Optical Networks

Sven Jager, Armin Zimmermann, and Ralph MaschottaSystem and Software Engineering Group

Computer Science and Automation DepartmentIlmenau University of Technology

Ilmenau, GermanyContact: see http://www.tu-ilmenau.de/sse/

Abstract—Model-based analysis and validation using simula-tion is a helpful tool in the engineering of complex systems. Thispaper presents a tool chain for the model-based architecturaldesign of avionic fiber-optic networks. A recently proposedframework for simulation-based domain-specific tools is the basisfor the development. It supports a model-based design workflowand offers a new 3D graphical user interface for location-basedconfiguration and result visualization of the underlying simulationtool. The benefits of the tool are validated with an applicationexample, in which different topologies for avionic fiber-opticalnetworks are evaluated and compared.

Keywords—System Design, Simulation, Tool Chain, 3D UserInterface, Avionics, Fiber-Optical Communication Networks

I. INTRODUCTION

Model-based systems engineering has shown its benefits inacademic and industrial projects, and is thus widely acceptedfor the design of complex systems. Among the reasons area reduction of costly failure corrections in late developmentstages caused by defective system specification documents andan increased overall system quality through early validation ofdesign decisions.

However, as general-purpose modeling tools become morecomplex, there is an increasing amount of system-specificknowledge in a design project involved. Domain experts usu-ally do not need all aspects and functional diversity of anunderlying general-purpose modeling and simulation environ-ment for their actual work. Thus, a simulation-based systemdesign and validation software tool is often needed for theactual system designers. This partitioning of responsibilitiesalso enables system designers to concentrate on their taskwithout the risk to introduce errors in the underlying systemmodel of given constraints.

Many components of such a simulation-based applicationcan be generalized, as they are typically involved in thistype of programs. Examples include modeling user interfaces,simulation modules, result visualization, common data stor-age in a data base, etc. A unifying framework enabling therapid development of extensible and reusable simulation-basedapplications has been proposed for this task recently [1].It supports an agile, iterative, evolutionary, and architecture-centric software development process. This paper presents

This work has been supported by a grant of the TU Ilmenau internalexcellency program 2013.

results on a new application domain (fiber-optical avionicnetworks) and its integration in the framework, the underlyingtool chain, as well as an additional 3D graphical tool for modelconfiguration and result presentation. The use of the tool isvalidated with a design example of nontrivial size.

Airlines and thus also aircraft manufacturers have a grow-ing interest in environmentally-friendly aircrafts, which areequipped with in-flight entertainment systems. Other innova-tive features of aircraft design include structural health moni-toring and adaptive maintenance. These example applicationslead to growing requirements on communication bandwidthand reliability, while power consumption and weight should bekept at a minimum. The present functional decomposition andchapter-based aircraft design as enforced by the Air TransportAssociation (ATA) leads to a set of independent communica-tion networks. While this eases safety certification processes, itis a very inefficient resource use compared to a jointly planned,integrated on-board communication network. The up-scalingof traditional copper networks is becoming cost-ineffective,since the increased weight leads to higher fuel consumption.The amount of bandwidth of merged communication streams,as well as low weight and independence of electromagneticinterference, makes fiber-optic technology [2] a promisingalternative, which is already used in parts of some aircraftdesigns [3].

The design of an integrated communication network has totake into account all requirements of several design chapterswhich are independently considered so far. The design taskresembles a global optimization of several subsystems andis obviously a hard task, which may benefit greatly from amodel-based engineering approach. A joint model of resourcesand requirements helps designers to base their local designdecisions on their effect on the global non-functional require-ments [4]. In [5], the benefits of a system design view onphotonic avionic networks aiming at several non-functionalproperties are discussed. The authors of [6] survey candidatephotonic network architectures suitable for embedded avionicsapplications, and propose an optical LAN-like bus structure.

Steps towards a necessary design process and tools for ithave been taken in the recently finished EU-funded projectDAPHNE1 (Developing Aircraft PHotonic NEtworks). Opticalnetwork components such as splitter/coupler devices, fibercable and multiplexer/demultiplexer for Wavelength Division

1c.f. http://www.fp7daphne.eu/

Multiplexing (WDM) were developed and simulated. The mainadvantage of a MBE approach is to simulate and evaluatea system at early design stages, and to avoid integrationissues caused by incomplete specifications. It differs fromprevious work, which has been focused mainly on physical-and lower-level models [7], [8], [9], by analyzing the networkarchitecture [10], [11].

Our earlier work presented in [11] covered a methodol-ogy and software tool capable of an automatic model-basedbandwidth planning for an integrated fiber-optical network.This is based on real-life subsystem requirements, and thetool then uses the derived link topology to compute end-to-end reliability figures (based on fault trees) to be comparedwith avionic design assurance levels (DAL). Moreover, metricssuch as delays, weight and cost of the integrated networkare computed. The underlying model describes functionalblocks, links, and their discrete-event behavior with the multi-formalism simulation tool MLDesigner [12], [13]. However,as many of the input data and computed results are tightlyconnected to the physical location of system elements insidethe aircraft body, the pure amount of data requires a graphical3D view for modelers and system designers to work with thetool efficiently.

The contribution of this paper includes a graphical domain-specific tool that has been developed for this task recently.Configuration parameters of the underlying simulation modelcan be selected and results visualized. Different aspects of onemodel can thus be described and analyzed in their own, verydifferent views, which is beneficial for system designers andmodelers. Moreover, an integrated tool chain for the involvedtools is introduced based on a framework of simulation-based system design tools [1]. The advantage of such a toolenvironment and model-based workflow is shown with anexample in avionic fiber-optical network design.

The paper is structured as follows. The architecture ofthe used software framework is recapitulated in Section II,including a description of the new 3D visualization componentin Section II-A and a design workflow supporting an integratedmodel-based design methodology (Section II-B). Section IIIintroduces an application example, in which different topolo-gies for avionic fiber-optical networks are modeled, evaluatedand compared. Finally, concluding remarks are given.

II. A SIMULATION-BASED SYSTEM DESIGN TOOL

It has been motivated in the introduction, why domain-specific implementations of simulation-based applications(i.e., software tools that support a model-based design viabehavioral models and performance evaluation) are beneficialfor system designers, who are often not experts in modelingand are concentrating on system-level decisions and structuralor parameter optimization of a planned system. To solve thisissue, it is important to hide the complexity of the simulationtool and the system model from this user group. However,an application (and proper user interface), which gives accessto the parameters and checks their complex dependencies,is necessary to select design options. Such a tool shouldalso control the simulation or other performance evaluationalgorithm, as well as analyze and present the results to theuser in a domain-specific way.

Fig. 1. Proposed general structure of simulation-based applications

To ease the development of such tools, a generic frameworkfor this class of programs has been proposed recently [1].Figure 1 depicts the general structure of such a simulation-based system design tool that we propose for such a situation.It can be integrated in an engineering design process for vali-dating configurations. An underlying modeling and simulationenvironment is wrapped by the application and controlled usinga simulation control interface. This interface needs at leastcapabilities to start and stop the simulation, and to accessmodel parameters and numerical results. The system model isused by the underlying modeling and simulation environmentand should be already developed before. Configuration dataand results of the simulations are stored in a specific database.The contents of the configuration database can be alteredand validated by the simulation-based application. During aperformance analysis, the simulation kernel reads the con-figuration, and writes the simulation results into the resultdatabase afterwards. Finally, the result database is read bythe simulation-based application to analyze results, compilevisualizations, and generate simulation reports.

A. 3D Visualization Plugin

A special requirement for the application area that has beenchosen here, i.e., fiber-optic network design in avionics, is thelarge amount of system design aspects that are based on ordepend on the resource location inside the aircraft fuselage.The system designer should concentrate on high-level archi-tectural decisions, and not be bothered with details which canbe automated with rules, such as the individual path planning

Fig. 2. Sample screen shot of the 3D visualization

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Fig. 3. Proposed workflow and corresponding parts of the tool chain (UML activity diagram)

of node-to-node links in the aircraft’s hull. Moreover, resultsand unresolved requirements should be visualized adequatelyand not just as a list of text. For this reason a plugin toour generic framework was developed, which visualizes thethree-dimensional positions of components and cables in thenetwork. Figure 2 shows a screen shot.

Beside the visualization, the plugin calculates routes andlengths of the fiber-optic cables of the network in 3D space.This is however an approximation, as it does not take intoaccount detailed CAD data and issues such as bundling andcorner bending. It reads the position of the components of thenetwork and the topology of the network from the database andgenerates a 3D model. Moreover, it calculates optimal routesand lengths of cables by using a constraint solver.

Our routing constraint is based on modeling the fuselageas a cylinder which is intersected by a plane (the cabin floor).Routing and placement for cables and components are onlyallowed on the cylinder or on the plane. There are threepossible routing directions on the 3D framework. On thecylinder, routing is allowed on a rectangular grid defined bythe so-called stringers and frames that stabilize the fuselage’sstructure, while cables can only be routed in the radial directionof the cylinder at floor level. This routing constraint is onlyan approximation of a future fiber-optic cabin hull. By movingthe routing code out of the model it is possible to integrate andcompare more complex constraints for the cable routing. Thecalculated cable length of each cable is stored in the databaseand is used to increase the accuracy of the simulation. Inaddition to that, it is possible to plot results on the 3D modelafter an analysis run in the simulation tool.

B. System Design Workflow and Simulation Tool

The tool architecture and the data/control flow for oursimulation-based system design tool sketched in Figure 1 isdescribed in more detail in this section. The components of thearchitecture and the data flow between them (which enforcesa certain workflow) is presented in the activity diagram inFigure 3.

The architecture consists of three parts:

1) The simulation tool MLDesigner [12], [13], [14], amulti-domain simulator, in which the model is builtand simulated; it allows the modeling of hierarchicalmodels by using block diagrams.

2) The database which stores configuration and results(c.f. Section II-C); and

3) the 3D configuration tool which calculates routes andlength of cables in 3D space, that has been explainedabove in Section II-A.

Modeling a network system requires adaptable buildingblocks, which are based on the functional network layer.A domain-specific MLDesigner library for fiber-optical net-works has been created in the DAPHNE project [11]. Thelibrary provides essential abstract building blocks for the mostcommon optical components like cables, switches, splitters,connectors and transceivers. The library supports modeling anddesigning fiber-optic network structures and layouts by usingcomponent and transmission medium models. Before a latersimulation, parameters of the building blocks are set to specificproperties of real hardware components based on configurationinformation. The resulting network models allow an evaluationof cost, weight, energy consumption, network load, latencyand packet loss. It can be used to calculate and estimate thenetwork’s relevant non-functional parameters to decide whicharchitecture or topology is the best one.

The workflow starts with the construction of the networkstructure in MLDesigner by using the abstract building blocksin the discrete event domain. To evaluate different topologies,each topology has to be modeled in its own MLDesignermodel. The building blocks are connected to each other, andthe user has to set design parameters such as the physicalposition of the components during the construction of thenetwork model. When the specification is finished, the networktopology is analyzed by the tool and end-to-end network routesare detected and planned for the necessary bandwidth as wellas saved to the database.

After creating the structure of the network, the parametersof the components and topology models can be accessed by theuser via the simulation-based application. The parameterizationof the network model requires several steps. Consequently,

the simulation progress is divided in three phases in order tocontrol the sequence and to prevent incorrect operations.

After calculating the length and routes of the fiber-opticcables, the user sets specific properties for the components inthe network. The GUI dialog for an example configuration isshown in Figure 4 as an example of application-level parametersetting for the user.

Fig. 4. Dialog for runtime parameter setting of fiber-optic network models

The simulation tool executes data transmissions during theconstruction of the network model. Messages are generatedby a triggered stochastic event. Each transmitter component istriggered in a particular interval and creates packets. On thereceiver side, the message is checked against destination andoptical power level. If the signal strength is not in the rangeof the specification, the receiver drops the packet and createsa record in the data base. The latency is calculated for eachend-to-end connection and saved in the database.

The last simulation step prepares simulation results toevaluate the designed network model. During simulation,MLDesigner continuously exchanges data with the data base.The latter stores simulation results including value, timestampand result ID for each event. Topologies can be studied interms of cost, weight and energy consumption.

The analysis of the simulation results is done in thesimulation-based application, which provides several possibil-ities including significant events plotted versus time, or theinfluence of a design parameter on a performance result in agraphical manner. It allows evaluating the results of a singletopology or to compare them after an experiment includingseveral topology models.

C. Data Base Integration

The data base (center of Figure 1) is the central pointfor data exchange between simulation-based application andsimulation tool with the system model.

Apart from the model configuration and simulation results,it can be used to store domain-specific data. In our exampleapplication, for instance, this includes hardware specificationsof possible links and nodes (splitters, couplers etc.) taken fromexisting products. The specifications are used to set attributevalues of abstract building blocks from the domain-specificMLDesigner library with real parameter numbers. MYSQL isused as the data base management system (DBMS) of our toolchain.

The data base may also serve in the future as a centralrepository for data exchange with other designers, and tointegrate the capabilities of the new tool into existing designsystems in the future.

III. AN APPLICATION EXAMPLE

Avionic network architecture design strongly depends onrequirements from aircraft manufacturers and regulatory bod-ies, and affects the economic efficiency of aircrafts. An inte-gration of different network systems requires high bandwidthfor applications such as in-flight entertainment (IFE). Anotheraspect which is important to aircraft manufactures and airlinesis the reduction of cost and weight as well as energy con-sumption. The network topology and architecture has a majorimpact on these properties.

The application example considers two different topologiesfor a fiber-optic network supporting the in-flight entertainment(IFE) system in an aircraft environment. The two topologiesare described first, before they are analyzed and results com-pared with the proposed tool. For simplicity, we choose asimple linear/bus topology and a bidirectional ring.

The system setup which does not depend on the actualnetwork solution and thus does not have to be optimizedis modeled first, as it stay constant for any actual networkarchitecture. We call this the null/zero topology model, whichis depicted in Figure 5.

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It consists of a head-end server in front of the cabin (leftside) and three consumer nodes for demonstration simplicity,one in the middle and two at the end of the cabin. For eachtopology, the positions and properties of these componentsremain the same. It can be imagined as constraints or partof the functional requirements that are given.

A. Linear Topology

The structure of the linear topology model in MLDesigneris shown in Figure 6.

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It consists of one bidirectional communication line withthe IFE server at the head of the cable. Three optical switchesare used as ”‘break out”’s for the passenger communicationsignal connections.

B. Ring Topology

The structure of the ring topology model shows Figure 7.

The composition of the network components and cablesbuild a ring with break-outs for passengers and IFE server.The topology is a bidirectional ring in which packets can flowin both directions along the ring. The components are arrangedin a symmetric way.

C. Configuration

The configuration of the model, i.e., setting of system-level parameters, is done in our simulation-based application.Therefore a domain-specific input window has been imple-mented as shown in Figure 4. For our example, each topologyuses the same specification for the base components, makingtheir attributes independent of the chosen architecture. Theparameters are listed in Table I.

TABLE I. CONFIGURATION OF THE COMPONENTS

parameter component name

cable type single mode

wavelength 1310 nm

cable Draka Bend 1310nm

transmitter 1310nm FP

receiver 1310nm Photodiode Enablenc SM

switch 1x2 Optical Switch

connector Connector KC

Beside the configuration of the network components, com-puting the routing of the cables is another important task of thesimulation-based application. The rule-based constraint solvermentioned earlier in the paper is used for the planning of cableroutes in the three-dimensional model of the cylindrical aircraftfuselage and floor.

The results are presented in Figure 8 and Figure 9.

Fig. 8. 3D view of the linear network topology in the configuration tool

For the linear topology the constraint solver routes thecable on one side of the cabin. The red components arethe transceivers of IFE server and consumers, while bluecomponents correspond to switches. Green lines representroutes of the fiber-optic cables. For the ring topology, the solverroutes the cables along both sides of the cabin.

Fig. 9. 3D view of ring topology links in the configuration tool

After the configuration, the simulation-based applicationstarts the underlying MLDesigner simulation for each topol-ogy, to analyze the non-functional properties of interest. Dur-ing the simulation, intermediate results are saved in the database for a later offline analysis.

D. Results

The results for cost, weight and energy consumption of thecomponents in the sample network for each topology are listedin Table II.

TABLE II. RESULTS FOR THE TOPOLOGIES

parameter ring linear

weight 20.3 kg 12.5 kg

cost 249.60 e 160.00 e

energy 1.154 W 0.694 W

Besides the accumulated results for cost, weight and energyconsumption it is possible to analyze performance parameterssuch as the packet latency over time for end-to-end connec-tions. This is shown in Figure 10 for the linear toplology andFigure 11 for the ring topology, and allows to check for bursts,transient behavior etc. in addition to standard properties suchas the mean or maximum value.

The plots are showing the overall end-to-end latency. Itis also possible to analyze the latency for each componentindividually. Moreover, bandwidth utilization per link hop(load) and packet loss in each component can be estimated.With these results it is possible to base decisions about whichtopology to choose on actual behavioral models and analyses.

This small example shows how our tool chain can beused to support the design process for fiber-optical networksby using individual models for different topologies, and asimulation-based application to configure, simulate and ana-lyze the model.

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IV. CONCLUSION

The paper presented an integrated tool chain for themodel-based design of avionic fiber-optic networks. Differentnetwork topologies and local design decisions can thus besemi-automatically planned and their effect on the overallsystem performance, reliability as well as other non-functionalproperties evaluated in an efficient way.

Its architecture is based on a recently proposed frameworkfor domain-specific simulation-based tools, and serves as anapplication example to prove its benefits. An integrated toolchain that hides the inner details from the user is presented,that supports a model-based design workflow. The underlyingfunctional block and discrete-event based simulation model inthe multi-formalism tool MLDesigner has been extended bya 3D user interface to ease configuration parameter editing aswell as result visualization of the underlying simulation model.

ACKNOWLEDGEMENTS

The authors would like to acknowledge the work of KarinSchulze on the avionic network model and earlier tool imple-mentation [11], the DAPHNE project consortium colleagues,and Yuwei Tian’s work on a 3D tool prototype [15]. The workhas been supported by a grant awarded in the TU Ilmenauinternal excellency program.

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