A Specification and Execution Approach of Flexible Cloud Service

Workflow based on a Meta Model Transformation

Imen Ben Fraj, Yousra BenDaly Hlaoui and Leila Jemni BenAyed

Research Laboratory in Technologies of Information and Communication and Electrical Engineering (LaTICE),

Institute of Sciences and Techniques of Tunis, Tunis, Tunisia

Keywords: BPMN Model, MDA Approach, Meta-model Transformation, Flexible Workflow, Cloud Service.

Abstract: Cloud environments are being increasingly used for deploying and executing workflow composed from

cloud services. In this paper, we propose a meta-model transformation for the specification and the

execution of cloud service flexible workflows. To built workflow abstract models, the proposed approach

uses a BPMN model for the specification of the cloud service workflow structure and the state-chart

diagram for the specification of the cloud service workflow behavior. In addition, workflow models should

be translated into BPEL4WS language which will be executed by the BPEL4WS engine, the latter is driven

by the behavior described by the state-chart diagram. To fulfill, we define a set of meta-model

transformations from the platform independent model (BPMN) to the platform specific model (BPEL4WS).

1 INTRODUCTION

1.1 Motivation

Cloud computing (Dillon and Chang, 2010) has

emerged in the distributed computing community, it

is mainly driven by the industry and has been largely

adopted by the research domain. The basic goal of

the cloud computing is to make a better use of

distributed resources and be able to solve large scale

computation problems. A cloud service is a web

service that provides a set of well defined cloud

interfaces and follows cloud specific conventions.

These services constitute a powerful basis for

modern application development. In order to enable

users to compose their applications without taking

care of the lower level details, the concept of cloud

workflow has emerged as a method for modeling

service applications (Yubin, Zeye, Zewei and

Ximing, 2013). The problem of building such

applications requires finding and orchestrating

appropriate services that is frequently a non trivial

task for a developer. This is due to the very large

number of available services and the different

possibilities for constructing a flexible workflow

from matching services. Flexible workflow is a

solution to fasten information system development

in distributed and dynamical environment like the

Cloud. Therefore, we propose in this paper a model

driven approach for automatic execution of flexible

workflow applications of cloud services using

BPMN model (Allweyer, 2010). Recently, several

solutions have been proposed to model applications

from cloud services such as works presented in

(Amziani, Melliti and Tata, 2013; Fengyu, Ying,

Zheng, Wei and Xilong, 2015).

However, the proposed solutions need interaction

with user and guidelines or rules in the design of the

composed applications. In consequence, the

resulting source code is neither re-usable nor it

promotes dynamic adaptation facilities as it should.

For applications composed of cloud services, we

need an abstract view not only of the offered

services but also of the resulting application. This

abstraction allows in one hand the reuse of the

elaborated application and on the other hand reduces

the complexity of the composed applications. There

are several architectural approaches for distributed

computing applications (Hu, Zhang and Yu, 2002)

which make easy the development process.

However, these approaches need rigorous

development methods to promote the reuse of

components in future cloud development

applications. It has been proven from past

experiences that using structured engineering

methods makes easy the development process of any

computing system and reduce the complexity when

Fraj, I., Hlaoui, Y. and BenAyed, L.

A Speciﬁcation and Execution Approach of Flexible Cloud Service Workﬂow based on a Meta Model Transformation.

DOI: 10.5220/0006338504670473

In Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017) - Volume 2, pages 467-473

ISBN: 978-989-758-248-6

467

building large cloud applications. To reduce this

complexity and allow the reuse of cloud service

applications, we adopt a MDA approach. The MDA

(Gronmo and Jaeger, 2005) approach developing

starts with defining high-level models in BPMN

(Allweyer, 2010), defines conversion rules from

BPMN to target platform, and then use code

generation to derive much of the implementation

code for desired platform.

1.2 Our Contribution

We propose a real time approach to built cloud

services applications by following OMG(s)

principals of the MDA in the development process

(OMG, 2005). In this approach, we are interested to

model and execute flexible workflows from existing

cloud services. The workflow modeling identifies

the resource from one depicted cloud service's

operation to the next to built and compose the whole

application. To model and express the composed

flexible workflow of cloud services, we define and

present in this paper a set of steps which begin from

the specification of the cloud service workflow

structure with BPMN and finish by processing the

flexible properties of the workflow model using the

real time meta-model transformation. In addition, we

propose a control system model which controls the

behavior of the BPEL engine based on the properties

of flexibility defined in a state-chart diagram using

the ECA rules (Hu, Zhang and Yu, 2002). The

provided model forms the Platform Independent

Model (PIM) of the proposed MDA approach.

Figure 1 presents the architectural view of the

proposed approach (Fraj, DalyHlaoui, Younes, and

JemniBenAyed, 2015). At the first step of the

approach, the user specifies its problem, i.e. the

result that it wishes to get from the workflow

composition, by modeling a composition request

using BPMN model (functional view). Another

specification of the cloud service workflow behavior

using a state-chart diagram (behavioral view) should

be defined. This request will be refined by the

composition system to built the composed workflow

from available cloud services. Before being

executed, two transformations should be produced

automatically, the first one is the transformation of

the BPMN model into a running platform model like

BPEL, the second is the transformation of the state-

chart diagram into a running platform using a

control system. Thus, we process the properties of

flexibility of the workflow model using the real time

meta-model transformation.

Figure 1: Architectural view of the approach.

1.3 Paper Reminder

This paper is organized as follows. Section 2

presents the related works. Section 3 details the

proposed approach for systematic cloud services

execution and section 4 presents the flexible

workflow and the properties of flexibility for cloud

services. Section 5 illustrates the specification

process based on the proposed BPMN model and

flexibility operator. Finally, section 6 concludes the

paper and proposes areas for further research.

2 RELATED WORKS

Several works and researches were carried out in the

field of modeling of flexible workflow of cloud

services like works presented in (Amziani, Melliti

and Tata, 2013; Fengyu, Ying, Zheng, Wei and

Xilong, 2015). In (Fengyu, Ying, Zheng, Wei and

Xilong, 2015) the authors propose a flexible UML-

based workflow model that is able to exhibit the

architecture of workflow engine and to adapt to the

changes of business process. They were based on

UML diagrams to describe the flexible workflow.

This approach would have been better if the

composition were automatically elaborated since the

number of available services is in increase with the

existence of several forms and manners to compose

such services. In (Amziani, Melliti and Tata, 2013),

the authors, propose a formal model elasticity for

service-based business processes (SBP). In this

model, processes are defined as Petri nets. Then,

elasticity operations (duplication and consolidation)

ICEIS 2017 - 19th International Conference on Enterprise Information Systems

468

are defined and heir correctness is proven. Each

service is represented by at least one place (the set of

places of each service are related with an

equivalence relation). The transitions represent calls

transfers between services according to the

behavioral specification of the SBP. The originality

of our contribution, relatively to this work, is that

first we save the user from the dynamic refinement

and execution as we propose an MDA approach

which separates the specific model from the

independent model. Second, we facilitate the

composition of flexible workflow as we guide the

user to compose her/his workflow using flexibility

patterns. Third, we consider the properties of

flexibility in the specification of the workflow in a

more natural way for the human user as we define

the functional and the behavioural views.

3 THE APPROACH OF

DEVELOPING COMPOSED

CLOUD SERVICES FLEXIBLE

WORKFLOWS

We propose a real time approach allowing the

specification and the execution of flexible workflow

applications composed from cloud services. The

specification is based on semantic knowledge of

cloud services and on the problem specification

which the user provides to the composer system.

There are three objectives to achieve by proposing

an architectural approach for developing distributing

computing applications:

1. ease the development process of such application,

2. enable rigorous development method,

3. promote the reuse of components.

To reach the first objective, our approach follows the

model driven architecture by separating the platform

development model from the platform specific

model. Thus, we propose to specify the workflows

model by a functional view using BPMN model

(Allweyer, 2010). The model provides an abstract

and understandable description of the cloud

application which is obtained from the integration of

cloud services in a workflow. The workflow model

will be validated and verified to ensure the reliability

of the future application before it is implemented

and that to save material and human costs. Also the

obtained models could be used as documentation for

further application extension. Figure 2 illustrates the

different steps and actions of the proposed approach.

Figure 2: Steps of the approach.

Specification Step. The flexible workflow is

modelled by a BPMN model based on different

patterns of composition of workflows. Each activity

represents the cloud service's operation that should

provide the result. At the same time, the

specification of the cloud service workflow

behaviour is also defined using a state-chart model.

The composition is described in an abstract level

using BPMN model (Allweyer, 2010) for functional

view and state-chart for behavioural view. Once the

two views are built, the workflow should be

validated and verified to ensure its reliability before

being executed and reused as sub-workflow. In this

paper we emphasize upon the modelling of

composed flexible workflows only from Cloud

services and not from sub-workflows.

Transformation Tool. This activity consists of two

actions: export execution code and export sub-

workflow description. The former transforms the

BPMN workflow model into its executable

workflow description by BPEL model. While the

latter translates the state-chart model describing the

behaviour of each properties of flexibility into its

matching control system like ADA (Woodruff and

Van Arsdall, 1998).

Execute the Flexible Workflow Application. The

workflow description document is sent to a

workflow engine that produces implementation code

for handling control-flow and data-flow. An

execution engine, such as BPEL4WS (Shen,

Grossmann and Yang, 2007) engine, executes

different workflow activities which are specified in a

workflow execution document in the correct order

and with their required input and output data. Before

execution, the engine consider the preliminaries and

requirements mentioned by the control system

model, the latter control the behaviour described by

A Speciﬁcation and Execution Approach of Flexible Cloud Service Workﬂow based on a Meta Model Transformation

469

the state-chart model. Thus, the real time meta-

model transformation is achieved.

4 FLEXIBILITY

4.1 Definition

The flexibility is the capability to implement

changes of the requirements in the business process

model and instances by changing only those parts of

the business process model and instances that reflect

the change.

Flexibility (Nurcan, 2008) has been the focus of

many researches (Regev and Wegmann, 2005;

Rosemann and Recker, 2006; Saidani and Nurcan,

2006; Schmidt, 2005). There are many definitions

of the flexibility in literature (Shi and Danies, 2003).

It is defined in (Regev and Wegmann, 2005) as “the

ability to yield to change without disappearing”. The

flexibility is the capacity of making a compromise

between, first, satisfying, rapidly and easily, the

business requirements in terms of adaptability when

organizational, functional and/or operational

changes occur; and, second, keeping effectiveness.

Processes

flexibility means fast reactivity to internal and

external changes. It reflects the easiness to make

evolve business process schemes (when required).

Flexibility is also reflected by the ability that the

support systems have to take into account business

changes.

4.2 Flexible Workflow

The flexibility refers to the executable ability to

flexible process definition by workflow management

system (WFMS). Flexibility of workflow means the

dynamic generation and modification on definition

of process instances during execution. Workflow

have to provide means to suit the flexibility and

adaptability requirements at any given time. Flexible

workflow management technology is one of the core

technologies to fasten information system

development in the cloud environments.

4.3 Flexibility Types

There are two types of workflow flexibility;

flexibility by modelling (a priori) and flexibility by

execution (a posteriori). The first type supports

dynamic selection for functional variability or user

interface variability of the cloud services. However,

the second one supports dynamic modifications in

different situations of the cloud service workflows.

It, also, adapts the workflow to the current situation

of the cloud during its execution.

The flexibility by modelling (a priori) (Nurcan,

2008) is based on modelling formalisms which can

offer the capacity to deal with the environmental

change without any evolution of process definitions.

This means that this capacity should be incorporated

in process definitions during build-time. It is based

on the dynamic construction of instances by

selection of components in a library. The process

instances are al-ways in conformity with the process

definition. This type of flexibility focus on the

specification of a flexible workflow execution

behaviour to express an accurate and less restrictive

behaviour in advance; flexible and adaptable control

and data flow mechanisms have to be taken into

account in order to support ad hoc and co-operative

work at the workflow level.

The flexibility by execution (a posteriori) (Nurcan,

2008) allows adapting the process definition or its

instances during their execution. This is the most

usual case in the literature. The principal challenge

is to know (i) when and according to which criteria

the adaptation should be done? (ii) in the type or the

instance level? (iii) ? how to deal with the instances

which are currently running? Approaches which

offer only this kind of flexibility are based on

prescriptive modeling formalisms. this type of

flexibility is provided by the change and evolution

of workflow models in order to modify workflow

specifications on the schema and instance level due

to dynamically changing situations of a real process.

4.4 Flexibility Properties

In this section, we present the properties of

flexibility, it can be achieved by three ways in which

the routing of cases along workflow tasks or cloud

services can be changed (Van der Aalst, 2001):

 Extend. Each cloud service has a maximal

capacity of treatment over that the QoS of

the service decrease and we risk to have a

breakdown, thus the solution

is adding

new tasks which (1) are executed in

parallel, (2) offer new alternatives, or (3)

are executed in-between existing tasks.

 Replace. An instance of cloud service

could be unavailable, so a task is re-placed

by another task or a subprocess (i.e.,

refinement), or a complete region is

replaced by another region.

 Re-order. A cloud service instance cannot

follow the order defined in the work-flow

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to reduce the execution time. Changing the

order in which tasks are executed without

adding new tasks, e.g., swapping tasks or

making a process more or less parallel.

Thus, flexibility in cloud service workflows remains

a solution for optimizing the cloud application

performance and running costs of cloud services.

5 ILLUSTRATION OF THE

EXECUTION OF FLEXIBLE

WORKFLOWS FROM CLOUD

SERVICES

In the following, we illustrate the execution process

through the example of an online computer shopping

service (Amziani, Melliti and Tata, 2013) composed

of four services :

 Service requests (S1): receives requests to

purchase a computer (processing time =

1s).

 Service components assembly (S2):

performs the assembly of computer

components according to the desired

characteristics (processing time = 60s).

 Service invoice (S3): creates the invoice

related to the purchased computer

(processing time = 1s).

 Service delivery (S4): delivers the computer

with its invoice to the customer (processing

time = 1s).

Figure. 3 models the normal workflow functional

behaviour, without considering the flexibility.

However, we can meet some problems during this

behaviour. These problems should be considered in

the functional model to predict any abnormal

behaviour.

Figure 3: Initial workflow.

We resume these problems as follows:

Problem 1: Each service has a maximal capacity of

treatment over what the QoS of the service decrease

and we risk to have a breakdown (Amziani, Melliti

and Tata, 2013).

Problem 2: In case of quality satisfaction , we are

with another copy of service, already create and

useless (Amziani, Melliti and Tata, 2013)..

Problem 3: In case of unavailable resource, the

process of the execution risk to fail.

The use of the flexibility properties is the solution

for these problems. We should update the initial

workflow model (e.g. the model of Figure 3) to

consider each of these properties based on the

behaviour parameter of the cloud service. We define

three modelling solutions:

Solution 1 (add): This solution consists in

duplicating (Amziani, Melliti and Tata, 2013) the

service to increase for treatment of requests. This

copy is created to treat the excess of requests.

Figure 4: Duplication of service S2.

Back to the initial workflow, the Service S2 has the

maximum time processing thus we can have an

overload on this service when it has a lot of calls, to

avoid that, we create a flexible workflow (Figure 4)

which contains a duplication of the service S2 into

S2-D when the condition is verified.

Our approach provide a real time transformation to

BPEL model by this code:

<partner="S2D.assembly"/>

<portType="GS2DPortype2D"/>

<operation="assembly"/>

</invoke>

<reply partner ="reply2" porType =

"GS2DPortype2d" operation ="assemby"

variable = "R2"/>

</case>

</event>

A Speciﬁcation and Execution Approach of Flexible Cloud Service Workﬂow based on a Meta Model Transformation

471

Solution 2 (delete): If the number of the requests

decreases, then it is necessary to delete the service

already created (Amziani, Melliti and Tata, 2013).

We create a new service which is responsible for

deleting the copy (Figure 5)

Figure 5: Delete of the service S2.

The transformation into BPEL is :

<partner="S5.delete"/>

<portType="GS5Portype5"/>

<operation="delete"/>

</invoke>

<reply partner ="reply5" porType =

"GS5Portype5" operation ="delete"/>

</case>

Solution 3 (resource): This solution consists in

adding new resource when the previous resource is

unavailable, after a delay of waiting , we should add

the new resource, to avoid the suspension of the

execution. (Figure 6)

Figure 6: Add resource for the service S3.

The corresponding transformation into BPEL

<partner="S3R.invoice"/>

<portType="GS3RPortype3R"/>

<operation="invoice"/>

</invoke>

<reply partner ="reply3" porType =

"GS3RPortype3R" operation ="invoice" variable

= "R3"/>

</case>

</event>

To be executed (See Figure 7), the composed Cloud

service application models which are Platform

Independent Models (PIMs) should be transformed

to Platform Specific Models. The specific platform

is the BPEL4WS (Andrews, Curbera, Dholakia,

Goland, Klein, Leymann, Liu, Roller, Smith,

Thatte, Trickovic, and Weerawarana, 2003)

platform. To achieve the objective, we propose a

meta-model transformation between different meta-

model languages used to specify the PIMs and the

PSMs of the composed Cloud service applications.

Figure 7: Meta-model transformation for executing

composed Cloud service workflow models .

ICEIS 2017 - 19th International Conference on Enterprise Information Systems

472

6 CONCLUSION

We have proposed an MDA approach for the

specification and the execution of cloud workflow

applications composed from cloud services. We

have detailed a set of steps for integrating and

matching, systematically, cloud services in a

workflow. In addition, we have presented a set of

properties of flexibility which are used in the

execution process to depict the right cloud service

to involve in the workflow. The approach shows also

how the modelling proposed constructs are applied

to model and represent a flexible workflow from

cloud services specified by BPMN to its running

platform by BPEL4WS. This process was illustrated

under the example of an online computer shopping

(Amziani, Melliti and Tata, 2013). As a proposal for

further work and with the objective to realize the

model-driven vision of OMG's MDA (OMG, 2005),

we need to develop a control system that verifies the

behaviour of the BPEL engine.

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