The Two-Hemisphere Modelling Approach to the Composition of

Cyber-Physical Systems

Oksana Nikiforova

, Nisrine El Marzouki

, Konstantins Gusarovs

, Hans Vangheluwe

Tomas Bures

, Rima Al-Ali

, Mauro Iacono

, Priscill Orue Esquivel

and Florin Leon

Faculty of Computer Science and Information Technology, Riga Technical University, Riga, Latvia

LIMS Laboratory, USMBA, Fez, Morocco

DMCS, University of Antwerp, Antwerp, The Netherlands

Department of Distributed and Dependable Systems, Faculty of Mathematics and Physics,

Charles University in Prague, Prague, Czech Republic

Dipartimento di Matematica e Fisica, Università degli Studi della Campania “Luigi Vanvitelli”, Caserta, Italy

Computer Science and Languages, University of Malaga, Malaga, Spain

Technical University "Gheorghe Asachi" of Iasi, Iasi, Romania

Keywords: Two-Hemisphere Model-Driven Approach, Cyber-Physical Systems, System Composition.

Abstract: The Two-hemisphere model-driven (2HMD) approach assumes modelling and use of procedural and

conceptual knowledge on an equal and related basis. This differentiates 2HMD approach from pure

procedural, pure conceptual, and object oriented approaches. The approach may be applied in the context of

modelling of a particular business domain as well as in the context of modelling the knowledge about the

domain. Cyber-physical systems are heterogeneous systems, which require multi-disciplinary approach to

their modelling. Modelling of cyber-physical systems by 2HMD approach gives an opportunity to

transparently compose and analyse system components to be provided and components actually provided,

and, thus, to identify and fill the gaps between desirable and actual system content.

1 INTRODUCTION

Cyber-Physical Systems (CPS) have never been

more central to the corporate strategy today. The

features they offer, reliability, performance and

robustness are the queens qualities that allow

companies to be competitive. To cope with the

complexity of the execution of such heterogeneous

systems, it is necessary to define an approach to

tame its complexity. This approach should be

flexible and generic in order to adapt to any type of

component of such system and thus, should offer an

ability to manage system composition.

The two-hemisphere model driven (2HMD)

approach has been successfully applied for domain

modelling and software design (Nikiforova and

Kirikova, 2004). One of the most distinguished

features of this model is its applicability for both

human understanding and automatic transformation.

In this paper we illustrate the way how 2HMD

approach may be applied to the task of modelling

and composition of CPS.

The goal of the paper is to show the way how the

problem of complex system composition from

smaller parts can be solved by using 2HMD

approach for modelling of CPS components. From

the point of view of 2HMD approach, each

component of a CPS may be considered as a

conceptual class, which preforms the particular

operations and meet the defined requirements. The

requirements are derived from the model that

consists of functional and conceptual “hemispheres”.

Thus 2HMD approach is applicable for both

modelling of components and modelling of the

process of to be supported by that component at the

same level of abstraction. Moreover, the 2HMD

approach can help to identify conflict situations,

where the additional analysis is required for sharing

responsibilities between system components.

Features of Cyber Physical Systems and the

necessity to model and compose them are discussed

286

Nikiforova, O., Marzouki, N., Gusarovs, K., Vangheluwe, H., Bures, T., Al-Ali, R., Iacono, M., Esquivel, P. and Leon, F.

The Two-Hemisphere Modelling Approach to the Composition of Cyber-Physical Systems.

DOI: 10.5220/0006424902860293

In Proceedings of the 12th International Conference on Software Technologies (ICSOFT 2017), pages 286-293

ISBN: 978-989-758-262-2

in Section 2. The essence of the two-hemisphere

model driven approach is clarified in Section 3.

Application of 2HMD approach for composition and

modelling of components of CPS are outlined in

Section 4. Conclusions are given in Section 5.

2 CYBER-PHYSICAL SYSTEMS

IN THE CONTEXT OF SYSTEM

COMPOSITION

A cyber-physical system (CPS) is a mechanism

controlled or monitored by computer-based

algorithms. In CPS, physical and software

components are deeply intertwined, each operating

on different spatial and temporal scales, exhibiting

multiple and distinct behavioural modalities, and

interacting with each other in a myriad of ways that

change with context (Khaitan, et al., 2014).

Being CPS inherently complex, any significant

analysis is a challenge. The behaviour results from

the different scales of the effect of the emerging or

fundamental phenomena, the different nature of the

components, the interactions and the drawbacks of

the internal compositions. A comparable domain is

System of systems (SoS), in which analysis exploits

decomposition (or, equivalently, design exploits

composition), and the system additionally exhibits

emerging behaviours or features that have to be

modelled at a higher level. While both for CPS or

SOS an holistic approach is viable for a general

understanding of the system from the point of view

of an external observer, in order to design or assess

in detail its behaviours the heterogeneity of the

problems that have to be analysed require that every

aspect and every component, and every scale and

every hierarchical subsystem, need a proper model

and a proper modelling technique. This is also a

natural consequence of the wide set of expertise that

has to be involved in the design, the maintenance

and the management of a CPS: every professional

takes care of a different aspect of a subsystem, using

a specialized view on it that privileges his

responsibilities and the modus operandi typical of

his field. Building up a comprehensive model of the

system could then benefit from the application of an

approach that allows model composition and use of

different modelling approaches together in a

coordinated framework, such as multiformalism

(Gribaudo and Iacono, 2014) or multiparadigm

(Vangheluwe, Lara and Mosterman, 2002)

modelling. For what is related to the design and the

analysis of non-functional specifications of system

components, some frameworks exist that allow

multiformalism modelling for non-functional

specifications by providing, by means of

metamodeling, the ability of designing new

modelling languages that can be naturally integrated

with existing ones and support modularity and

multiformalism: e.g., the SIMTHESys approach

(Barbierato, Gribaudo and Iacono, 2011) explores

these possibilities and is being extended to include

also support for a domain, hybrid systems

(Barbierato, Gribaudo and Iacono, 2016), that

includes CPS. The main directions behind this

approach aim to decouple whenever possible the

state spaces of the various components (with

significant results in favourable cases (Barbierato, et

al., 2013)), build natural interactions between

models written in different modelling languages, and

representing emerging properties of the overall

model. Leveraging this experience, it is possible to

abstract the main ideas and take inspiration for

implementing ideally similar compositional and

modular features in modelling approaches that focus

on aspects that are different from non-functional

specification. In this paper we want to discuss the

applicability of some of the concepts here presented

about non-functional specifications to a more

abstract modelling domain, specially focusing of the

perspective that allows the application of the 2HMD

approach. CPS involves transdisciplinary

approaches, merging theory of cybernetics,

mechatronics, design and process science (Hancu, et

al., 2007), (Lee and Seshia, 2011), (Suh, Carbone

and Eroglu, 2014). The process control is often

referred to as embedded systems. In embedded

systems the emphasis tends to be more on the

computational elements, and less on an intense link

between the computational and physical elements.

CPS is also similar to the Internet of Things (IoT)

domain, sharing the same basic architecture;

nevertheless, CPS presents a higher combination and

coordination between physical and computational

elements (Rad, et al., 2015). As far as CPS are

multidisciplinary heterogeneous systems, their

implementation requires a strategy for modelling

and decomposition into smaller components. The

components of such systems then should be detailed

at the same level of abstraction.

One of those systems is Ensemble Component-

Based Systems (Bureš, et al., 2013), (Keznikl, et al.,

2012), where components are autonomous and the

communication is implicit. Needless to say that

emergent systems as an up-and-coming systems

introduce new concepts for design (Bureš, et al.,

2013), (Hennicker and Klarl, 2014) as well as for

The Two-Hemisphere Modelling Approach to the Composition of Cyber-Physical Systems

287

whole system development process (Carloni, et al.,

2005). Working with such distributed systems

require dynamicity and scalability with reserving to

the autonomous behaviour in each component. This

allows designers to have their focus on individual

components and to work on developing each of the

following separately: 1) the component structure and

behaviour, 2) the implicit connector called

ensemble, and 3) the link between computational

and physical elements for each individual alone.

ECBSs are dynamic systems, which require

composition and decomposition of its components

and ensembles depending on the context. These

systems offer a combination of both architectural

and behavioural models to represent such

decomposition in their structure, providing by that

the ability to analyse and verify satisfaction of their

requirements. Moreover, the methodology in this

modelling approach considers each component in

the system as a black box. More specifically, each

component features a set of roles where each one

serves as an interface in the communication. Each

role consists of a set of data fields called knowledge

and mode-switch table (Bureš, et al., 2016). In the

knowledge section, an enumeration of component

modes is presented as a data field. Hence, the

behaviour of the component is held in the mode-

switch table that has all the context constraints and

their corresponding modes.

It is worth mentioning that each mode is

associated to a set of processes in the component

that is executed when the mode is active.

Furthermore, the component has sub-components

that are captured in the structure as data fields. By

setting this data field, it is possible to build a

hierarchical component (i.e. the data field could hold

a null value). Although the structure of the

components represents (de)composition structure, it

does not capture the (de)composition process; it is

only describing the flow of activities in an

autonomic component of the system using mode-

switch table for each role that the component

features. Simply put, the role activity diagram will

have the knowledge on the transitions and the modes

as activities. Therefore, a mode-switch table in the

architecture is a representation of the behaviour of

the component role. Regarding the (de)composition

process, ensembles are responsible for it, since they

form between the components that have specific

modes and exchange the knowledge between them.

The ensembles have three basic structures: 1) the

roles and their current modes of the components, 2)

the context as a membership condition, and 3) the

knowledge exchange. Hence, the ensemble

behaviour is held in the knowledge exchange part,

which is guarded by corresponding constraints (i.e.

roles or mode in the roles, and membership

condition). Ultimately, ensembles have a

hierarchical structure due to hierarchical structure of

their components (Bureš, et al., 2015).

Finally, in those terms, (Al Ali, et al., 2014) and

(Bureš, et al., 2016) introduce approaches to capture

the internal and external uncertainty in the system,

and to handle it during the adaptation process by

linking the physical elements in the same abstraction

level as computational ones. In (Al Ali, et al., 2014),

this is applied to Ordinary Differential Equations

(ODE) for physical objects at the process level. The

goal is to capture the impact of delays, which are

caused by networks or computational parts, on

physical elements (i.e. actuators). The method

enhances the prediction of the real state boundaries

of each physical object.

About the same problem, (Bureš, et al., 2016)

targets the uncertainty caused by sensor readings,

where the precision of sensed data is the main

concern. The effect of data precision is represented

in a self-adaptation process, where the authors

extend mode-switch logic to involve statistical

testing. The extended logic applies hypothesis

testing over historical data to evaluate the condition

in mode-switching with a certain confidence level. It

is worth mentioning that mode-switch conditions

deal with short time prediction as well as the current

situation. At the end, both kinds of uncertainty are

captured explicitly in the architectural view, making

it possible to apply traditional analysis and

transformations with a minimum amount of

modification on the existing tools. Similarly, we can

discuss the issue of composition in the context of

multiagent systems. Sometimes, the complex

interactions between the individual agents give rise

to an emergent behaviour of the system as a whole,

e.g. in modelling social systems, traffic simulations

etc. However, other applications can benefit from

system composition, e.g. agent-based business

process modelling. A tool that is often used in this

situation is the visual notation of Role-Activity

Diagrams (Ould, 2005). They contain roles, which

describe the behaviour of a set of role instances.

Roles have states, similarly to dynamic systems. A

business process may contain one or more active

instances of the same role. An actor is an agent that

enacts a role instance. Activities are the basic

building blocks of a role. Carrying out the activities

of a role can be interpreted as transferring the

process control from a state to another state. An

activity may be carried out in isolation or may

ICSOFT 2017 - 12th International Conference on Software Technologies

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require coordination with activities in other roles,

and in this case it is an interaction. Some studies

showed that this class of workflows can be

formalized and modelled by a concise set of distinct

rules in a generic knowledge-based business agent

architecture (Badica, et al., 2016) and can be

implemented using both agent-oriented languages,

such as Jason, and general-purpose functional

languages, such as F# (Leon and Badica, 2016).

3 TWO-HEMISPHERE

MODEL-DRIVEN APPROACH

The variety of modelling capabilities and the ability

to express links traceability are decisive assets to

manage system’s complexity. The transformation

tool takes one model as input and produces a second

model as its output. The two hemisphere model

driven approach (Nikiforova and Kirikova, 2004)

proposes the use of business process and concept

modelling to represent systems in a platform

independent manner and describes how to transform

them models into UML models, shown in Figure 1.

The choice and design of these diagrams is not only

based on the previously mentioned analogy with the

human brain, but also due to the fact that

information shown in these diagrams helps to

describe the system from the two different points of

view that we believe to be able to capture the most

relevant aspects in system development. Business

process modelling, as (Polak, 2013) mentioned,

developed as a result of solutions made by

Management Science and Computer Science in the

1970s, and keeps showing its importance in

supporting process modelling and analysis. The

importance of business process modelling is

confirmed by (Harmon and Wolf, 2014) regular

researches about the usefulness and usability of

these processes. Results confirm that management of

business processes is valuable for companies and

that firms progressively adopt existing business

process modelling notations and methodologies.

Figure 1: The essence of the two-hemisphere model transformation.

The Two-Hemisphere Modelling Approach to the Composition of Cyber-Physical Systems

289

Consequently, the two-hemisphere model

benefits from the incorporation of well-known

business process tools and lowers, at the same time,

the gap between existing and needed internal

knowledge and procedures. As the two-hemisphere

model serves as a bridge between problem domain

and software design phase, business model is

understandable to both sides - business people and

developers. The inclusion of a conceptual model in

the approach is motivated by the principles of the

object-oriented paradigm and general context of data

analysis. In many widely accepted software design

approaches, in the first phases of the development

cycle a data dictionary is created or an analogous

document defines a shared agreement about

terminology used in software development and

documentation. (Johnason and Henderson, 2011)

describes conceptual modelling as the basis of

software development, absolutely needed to produce

a quality design. Conceptual models are high-level

software description, which contains concepts. Any

kind of things, events and living beings that are

important to given problem domain can be

considered as concepts. Concepts are described with

attributes, but methods shows actions specific to

these concepts. An early and consolidate example of

conceptual models is Peter Chen’s (Chen, 1976)

Entity-Relationship (ER) diagrams, used in database

design (Hesse, 2007), and, later, in software system

design. Consequently, a natural choice for the other

part of the two-hemisphere model is a conceptual

model, consisting of concepts and related attributes,

with a model notation similar to ER diagrams.

4 THE TWO-HEMISPHERE

MODEL-DRIVEN APPROACH

FOR SOLVING COMPOSITION

PROBLEMS

The strategy of the two-hemisphere model-driven

approach supports gradual model transformation

from problem domain models into program

components, where problem domain models reflect

two fundamental things: system functioning

mechanisms (processes) and structure (concepts and

their relations). Several two-hemisphere models

presenting different aspects of CPS and its

components structure and behavior have been

marked as input with mapping rules, the class

diagram and transformation trace has been received

on output (see Figure 2). Transformation trace

shows how an element of the two hemisphere model

is transformed into the corresponding element of the

class diagram, and which parts of the mapping are

used for transformation of every part of the two

hemisphere model (Nikiforova, 2009).

The model decomposition into small components

and composition of them as an integrated system is a

new research topic for two-hemisphere model-driven

approach, originally introduced in (El Marzouki, et

al., 2016). The work is under ongoing development

and evolution, consequently, there is still no mature

foundation to date for this. Our goal through the

research on the composition of CPS is to study

existing models of composition approaches by

analysing and identifying: 1) what are the elements

involved in the composition process, and 2) how the

model composition is made in these approaches.

The ultimate goal is to arrive at an understanding

of what is done for model composition in these

approaches. "Model composition is an operation that

combines two or more models into a single one."

(Cavallaro et al., 2010) "Model composition in its

simplest form refers to the mechanism of combining

two models into a new one." (Dubre and Dixit,

2012) According to this, it can be said that the

composition model is a process that takes two or

more input models, integrates them through an

operation and composition to produce a composite

output model. However, this scheme is very abstract.

No assumptions about the input models, output, or

on the compositing operation is expressed. In

practice, each approach must specify these

assumptions for its work context. These also include

the differences to classify approaches:

• Mechanism of composition: melting, replacing

the union, weaving etc.

• Element composition: what are the additional

elements involved in the composition. There

are two classification axes: the type and

formality of these.

• Language of composition: The composition of

elements need formalisms to express them.

These formalisms are very diverse because each

approach has its own elements of composition. They

can be a weaving language, a metamodel of

composition rules, a UML profile for model

composition, etc (Dubre and Dixit, 2012). Despite

their diversity, they can usually assess a

compositional formalism on two points: the

composition that provides abstractions and

scalability.

ICSOFT 2017 - 12th International Conference on Software Technologies

290

Target modelSource model

Process Model Concept Model

Class

Diagram

Two-hemisphere model

based transformation

definition

Transformation

Tool – BrainTool

Two-hemisphere model

Two-hemisphere model-drive approach

Target model

PM for CPS

component 1

CM of all the

components of CPS

Class Diagram for

integrated CPS

Two-hemisphere model

based transformation

definition

Transformation

Tool – BrainTool

Two-hemisphere model

Application of the approach for composition of CPS

PM for CPS

component 2

PM for CPS

component M

PM for CPS

component N

Source model

Figure 2: Adoption of the two-hemisphere model-driven approach to composition of CSP.

To synthesize, we can define the composition as

a model management operation, which generates a

single model by the combination of the contents of

at least two models:

• Syntactic level: Expression model compound

from input models;

• Semantics level: Assigning a semantic model

compound, depending on the semantics of the

associated source models;

• Methodical level: Using the model compound,

derived from the composition process in a

software development process.

Therefore, the composition process cannot be

considered as an atomic operation. Before triggering

the composition process itself, it is necessary to

identify the links between the elements composing;

hence the emergence of the pre-match phase

followed by a composition operation that aims at the

creation of the model "global" by combining

elements using input patterns of relationships

defined in the matching pattern.

So, considering all these all these criteria, it is

clear that making a survey on composition

techniques and identify their gaps seems an

interesting path to build a new composition models

operations based on two hemisphere model

approach. In other words, we suggest using this

taxonomy to create a novel composer framework to

resolve composition conflicts for a given problem.

So now, we are also studying the made to take

into account the semantic properties of models. If we

take the example of two operations in two models

that appear with the same signature (name, type,

parameters), so to remedy this problem, we must

either include a step of reconciliation between the

separate designs or strengthen semantics associated

with the input metamodel, so that we can implement

finer comparison strategies that address the

behaviours described by the methods.

5 CONCLUSIONS

The evolutionary nature of CPS aims at building

cross-domain intelligence, in heterogeneous and

dynamic contexts (Khaitan and McCalley, 2015)

(Wu, Kao and Tseng, 2011). For this reason, CPS

composition should focus on the interactions

between the control logic and the physical systems,

contemplating the possibility of limited information,

e.g., stability, safety, performance, timeliness, etc.

CPS composition can be performed according to

different criteria, from the CPS itself which is a

schema of CPS as systems of systems (Nazari,

Sonntag and Engell, 2015), to a hierarchy of

components at the architectural level (Bhave, et al.,

2011). The common feature among the different

composition approaches is how they encapsulate the

cyber and physical aspects through an infrastructure.

The Two-Hemisphere Modelling Approach to the Composition of Cyber-Physical Systems

291

The latter should allow the integration of CPS

concerns and, also provide support for the

orchestration of a larger system architecture. In turn

to manage the process of CPS integration the

strategy of CPS components' composition became

the important task for CPS modelling. The model

composition is the central concept also in model

driven architecture for maximizing return on

investment, dealing with complexity and

maintainability. This paper discusses abilities on

adopting a new methodology presented in the form

of a conceptual prototype to automatically compose

models defined in terms of class diagrams in order to

build a global view of the system under construction.

We have presented the progress process on model

composition based on the two hemisphere model

driven approach introduced in (Nikiforova and

Kirikova, 2004). The idea is focusing on model

composition paradigm as a crucial activity. The

composition of CPS is applied based on two-

hemisphere model driven approach, which is an

approach that aims to automate the process of class

diagram development from correct and precise two-

hemisphere model and enables knowledge

representation in a form understandable for both

business users and system analyst. As far as the two-

hemisphere model-driven approach allow to share

responsibilities among object classes and to define

the relationships between them, we can consider that

for CPS we can define: 1) the general schema of

their components (the same as classes for object-

oriented system), 2) how to share

responsibilities between them, i.e., to define which

processes will be performed by which components,

and 3) structural relationships among CPS

components (as well as dependencies) within the

task of their implementation.

The central hypothesis of two-hemisphere

model-driven approach is to apply many

transformations for composition of the complex

system from small parts, where each of them

presented as the source model is defined in terms of

a business process model, associated with a concept

model, and the target model is defined in terms of

class diagram, which is generated for the whole

system. When the models are small enough and

developed by a single or a couple of designers, they

can be composed manually. However, in the case of

cyber-physical system, the models are too large to be

composed manually and it’s necessary to develop an

automatic composition method to ensure that all the

elements in the model are handled. In this paper we

have only taken into account the conceptual part of

our methodology, thereby the authors try at the

moment to investigate the possibility to implement

the proposed technique as an open source tool using

ATL Language. The idea of conceptual composition

prototype described in this paper currently can

handle not only homogeneous models, those that

share the same meta-model, it would be interesting

to extend this approach to handle heterogeneous

input models as well.

As a future work to what is presented in this

paper we are currently investigating a finer-grained

redefinition of every module of CPS separately, the

first one will be a repository dedicated to the

resolution of potential composition conflicts. This

allows focusing on any type of conflicts that requires

special treatment, thereby it will facilitate the

generic implementation of the other modules.

Another line of future investigations concerns the

model comprehension aspects of our model

composition technique. The benefits for model

comprehension address in particular the reverse

process of building model hierarchies. We hope you

find the information in this template useful in the

preparation of your submission.

ACKNOWLEDGEMENTS

This publication was developed in frame of COST

Action IC1404 Multi-Paradigm Modelling for

Cyber-Physical Systems and with minor revisions is

published by Departamentos Lenguajes y Ciencias

de la Computación, Universidad de Málaga in

Proceedings of the 4th Workshop of the MPM4CPS

COST Action as Technical Report No. ITI16/01.

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