Labeled generalized stochastic petri net Based approach for web services Composition

International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 3, June 2013
DOI : 10.5121/ijcsit.2013.5312 151
LABELED GENERALIZED STOCHASTIC PETRI NET
BASED APPROACH FOR WEB SERVICES
COMPOSITION
Sofiane Chemaa1
, Mouna Bouarioua2
and Allaoua chaoui3
MISC Laboratory, Department of Computer Science and its applications, University of
Constantine 2,Constantine, Algeria
1
chemaa@misc-umc.org
2
bouarioua@misc-umc.org
3
a_chaoui2001@yahoo.com
ABSTRACT
A Web Service is a component written in any language, deployed on any platform, which has a standard
wrapping layer based on XML.The component can interact with other applications which themselves
comply with the Web Services standards. Generally, a single service does not satisfy the users needs that
are more and more complex. Therefore, services must be made able to becomposed to build new value
added services. This process is called Web services Composition. This latter is a critical subject that
requires formal techniques for its completion. In this paper, we show how basic and existent services can
be composed to create a composite service which offers a new functionality. In this context, we propose an
expressive Labeled generalized stochastic Petri net based algebra that succeeds in the complex Web
services composition. Basic and advanced constructs which are supported by the proposed algebra are
syntactically and semantically defined.
KEYWORDS
Web Services, Web services composition, LGSPN, Algebra, formal techniques.
1. INTRODUCTION
Nowadays, web services present a new vision of the provision of software components for
information systems. The concept of Web service essentially refers to an application made
available on Internet by a service provider and accessible by clients through standard Internet
protocols such asSimple Object Access Protocol (SOAP) [1], Universal Description, Discovery
and Integration (UDDI) [2], and Web Service Description Language (WSDL) [3].The
composition of Web services is a natural evolution of this technology and has enormous potential
in reorganizing business-to-business or enterprise application integration. Current technologies
based on WSDL, UDDI and SOAP offer solutions for description, publication, discovery and
interoperability of Web services; but do not accomplish their complex composition that remains a
very complex task, and requires formal techniques for its accomplishment.
In this paper we address the Web service composition problem using a Petri net based framework
called Labeled Generalized Stochastic Petri Net (LGSPN) [4]. Compared to other approaches,
this concept offer efficient and powerful mechanisms for complex systems modeling which are
not supported even by high level Petri nets. In this context, we propose a LGSPN based algebra
for composing Web services that successfully solves complex composition. The proposed

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approach provides not only a formalism to describe Web services structure and behavior but also
a representative set of operators presented by means of syntax, semantics and the resulting
composite service. The choice of the LGSPN models is justified by many reasons. For example:
• The use of visual modeling techniques such as LGSPN in the design of complex Web
services helps us to easily understand the modeled services.
• The modeling based on LGSPN allows the specification and prototyping of complex Web
services with taking into account the time constraints.
• LGSPNs provide a formalism that allows the construction of models that can be used for
behavioral analyses based on the classical theory of Petri nets, and also for Performance
analyses based on the time specifications and the probabilistic models.
The remainder of this paper is organized as follows. Web service modeling and specification
using LGSPN are presented in Section 2. An expressive algebra that permits to compose Web
services modeled with LGSPNs is given in Section 3. In Section 4, we give a brief overview of
some related work. Finally, we discuss in Section 5 some prospects and work in progress.
2. Web services as Labeled generalized stochastic Petri nets
A Petri net (PN) [5] isa graphical and mathematical modeling tool. This is a directed bipartite
graph with two types of nodes: places are represented by circles and transitions are represented by
rectangles. The arcs of the graph connect places and transitions in such a way that places can only
be connected to transitions and vice versa. Places in a Petri net may contain a discrete number of
tokens. The distribution of tokens over the places is called a marking.
When Carl Adam Petri has introduced Petri nets in his thesis for the first time, they had served to
describe concurrent systems in terms of cause / effect relations without considering the notion of
time. The introduction of temporal concepts into Petri nets was proposed several years later by
other researchers. The transition firing is the result of either a logical condition becoming true in
the system, or the achievement of an activity. The latter interpretation is the reason for associating
timing with transitions. The resulting paradigm from the introduction of temporal concepts into
classical PN is a sub model called stochastic Petri nets (SPN) [4]. When stochastic timing is
mixed with deterministic null delays, we obtain generalized stochastic Petri net models (GSPN).
In the case where each transition is labeled, the model is called labeled generalized stochastic
Petri nets (LGSPN). For more details about the LGSPN, the reader is referred to [4] and [6].
Web services are assimilated to a distributed system; that consists of a set of loosely coupled
modules, which communicate through messages exchange. The behavior of a web service is
defined by a set of operations. Thus, modeling Web services using LGSPN is straightforward.
Every operation in the service is modeled by a transition; the state of the web service is modeled
by the position of tokens in the LGSPN and the arrows between places and transitions are used to
specify causal relations.
In the following, we give some formal definitions about LGSPN-Service and Web service.
2.1. LGSPN-Service
To simplify and facilitate the web services modeling using LGSPN models, we have made some
modifications to the LGSPN notation defined in [6]. As a result we present the LGSPN-Service
Models.

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A LGSPN-Service is an 11-tuple − = ( , , , , , , , , , , ) where:
• is a finite and non-empty set of places.
• = ∪ is a finite set of transitions where: IT is a set of immediate transitions
denoted by a black rectangle. TT is a set of timed transitions denoted by an empty
rectangle.
• : → ℕis the priority function. It associates a priority level to each transition.
Let ∈ , ( ) = 0 if .type = TT and ( ) > 0 if .type = IT. (i.e. the firing of an
immediate transition has priority over the firing of a timed transition).
• , , : → ( ) | ( ) ⊆ are the input, output, and inhibition functions.
• : → ℝ is a function defined on the set of transition. W allows the definition of the
stochastic process associated with the model.
• is the initial marking of the LGSPN-Service.
• is the input place with ● = { ∈ T| ∈ ( ) } = Ø.
• ois the output place with ●= { ∈ T| ∈ ( )} = Ø.
• ∶ → ∪ { }is a labeling function where is a set of operation names and is a
silent operation (unobservable operation). In this work, we have modeled a silent
transition ( ) by an immediate transition with ( ) = | ∈ ℕ∗
and ( ) = | ∈
ℝ .
In figure 1(a), we propose an example that illustrates the principle of LGSPN-Service models.
The service reproduces the behavior of a translation system. After reading an English text, the
system activates two other local processes in parallel. The first process allows to translate the text
in French. The other process enables the translation of the same text in Spanish. Once the two
translations are completed, a correctness check process is activated.
In this example we have 4 temporal transitions (t1, t3, t4, t5) and an immediate transition (t2).
This latter represents the action of the activation of the two translation processes in parallel. This
action is modeled by an immediate transition because its execution time is negligible.

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Figure 1. LGSPN-Service Example (a); Services S1,S2,S3 (b)
2.2. Web Service
A Web service is a tuple [7] where:
• NameS is the name of the service used as its unique identifier.
• Desc is the description of the provided service. It summarizes what functionalities the
service offers.
• Loc is the server in which the service is located.
• URL is the invocation of the Web service.
• CS is a set of the component services of the Web service, if CS = {NameS} then S is a
basic service, otherwise S is a Composite service.
• is the LGSPN-Service modeling the dynamic behavior of the service.
In the next section, we propose an algebra that permits to incrementally compose existing web
services modeled byLGSPNs. The aim is to create a new composite service that provides new
functionalities.
3. Web services Composition
Web services as presented, are components, conceptually limited, with relatively simple
functionalities, which are modeled by a set of operations [8]. Given two or more Web services,
each with a specific task,they sometimes cooperate in order to achieve a new task.This will result
in a new value added service. For example aservice of hotel booking can collaborate with a Web
mappingservice like Google Maps API to show the location of hotels tothe customers. The
(b)
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collaboration of these services generates acomposed Web service which performs the original
individualtasks as well as a new one.
In this section we present an algebra that combines existing Web services for building more
complex ones. We will take Sequence, Parallel, Alternative, Iteration and Arbitrary Sequence as
basicconstructs. Moreover, two more developed constructs which are Discriminator and
refinement are defined. After that, each operator formal semantics in terms of LGSPN-Service is
given.
3.1. LGSPN-Service based algebra
The BNF-like notation below describes a grammar defining the set of services that can be
generated using algebra’s operators.
S:: = ε | X | S► S | S◄►S | ↺ S | S ⇔ S | S//S | (S ⊡ S) ≫ S | ( , , ).
Let = ( , , , , , )
with = ( , , , , , , , , , ) for i = 1...3 be three Web Services such that
∩ = Ø and ∩ = Ø for ≠ .
Empty Service ( ): The empty service ε is a service that performs no operation. It is used for
technical and theoretical reasons.
Definition 1 The Empty service is defined as ε = ( , , , , , )
where:
 = Empty.
 = “Empty Web Service”.
 = Null, stating that there is no server for the service.
 = Null, stating that there is no invocation for the service.
 = {Empty}
 = ( , Ø, Ø, Ø, Ø, Ø, Ø, Ø, , , Ø).
In Figure 2(a), we show the graphic representation of the empty service (ε) in terms of LGSPN-
Service.

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Figure 2. Empty Service(a); Sequence Service (b); Alternative Service (c)
Sequence (►):The sequence operator permitsto execute two services successively. This operator
can be used in the case where a service depends on the execution results of another service. For
example, in an online purchase operation, the service "Order" must be executed before the
service "Payment".
Definition 2 The serviceS ►S is defined asS ►S = ( , , , , ,
) where:
 = ∪
 = ( , , , , , , , , , , ) where:
= ∪ , = ∪ ∪ { }, = ∪ ∪ {( , )| ∈ ℕ∗}, = ∪ ∪ {( , )},
= ∪ ∪ {( , )}, = ∪ , = ∪ ∪ {( , )| ∈ ℝ },
= ∪ , = , = , = ∪ ∪ {( , τ)}.
Given the two services and shown in Figure 1(b), the composite serviceS ►S is
represented by the LGSPN-Service shown in Figure 2(b).
Alternative (◄►): Given two services and , the alternative operator reproduces either the
behavior of or , but not both. This operator is also called “choice operator”.
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Definition 3 The service S ◄►S is defined asS ◄►S = ( , , , ,
, ) where:
 = ∪
 = ( , , , , , , , , , , ) where:
= ∪ ∪ { , }, = ∪ ∪ { , , , } , = ∪ ∪ {( , ),
( , ), ( , ), ( , )}, = ∪ ∪ {( , ), ( , ), ( , ), ( , )},
= ∪ ∪ {( , ), ( , ), ( , ), ( , ) }, = ∪ , =
∪ ∪ {( , ), ( , ), ( , ), ( , )| , , , ∈ ℝ }, = ∪ ,
= ∪ ∪ {( , τ), ( , τ), ( , τ), ( , τ)}
Given the two services and shown in Figure 1(b), the composite service S ◄►S is
represented by the LGSPN-Service shown in Figure 2(c).
Figure 3. Iteration Service(a); Arbitrary Sequence Service (b); Parallel Service (c)
Iteration (↺): The iteration operator allows the service S to be performed a certain number of
times in a row. For example, this operator can be used in the case where a client performs several
successive orders.
Definition 4 The service ↺ is defined as ↺ = ( , , , , , )
where:
 =
 = ( , , , , , , , , , , ) where:
= ∪ { , }, = ∪ { , , } , = ∪ {( , ), ( , ), ( , )},
= ∪ {( , ), ( , ), ( , )}, = ∪ {( , ), ( , ), ( , ) },

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= , = ∪ {( , ), ( , ), ( , )| , , ∈ ℝ }, = ,
= ∪ {( , τ), ( , τ), ( , τ)}
If we consider the service shown in Figure 1(b), the composite service ↺ is represented by
the LGSPN-Service shown in Figure 3(a).
Arbitrary Sequence (⟺):Given two services and , the Arbitrary Sequence operator builds
thecomposite service ((S ►S )◄► (S ►S )). The latter is useful when the services execution
order is not important and there are no benefits to execute services in parallel.
Definition 5 The service S ⟺ S is defined as S ⟺ S = ( , , , , ,
) where:
 = ∪
 = ( , , , , , , , , , , ) where:
= ∪ ∪ { , , , , , , }, = ∪ ∪ { , , , , , } ,
= ∪ ∪ {( , ), ( , ), ( , ), ( , ), ( , ), ( , )}, = ∪ ∪
{( , ), ( , ), ( , ), ( , ), ( , ), ( , ), ( , ), ( , ), ( , ),
( , )}, = ∪ ∪ {( , ), ( , ), ( , ), ( , ), ( , ), ( , ),
( , ), ( , ), ( , ), ( , )}, = ∪ , = ∪ ∪ {( , ), ( , ),
( , ), ( , ), ( , ), ( , )| , , , , , ∈ ℝ}, = ∪ , = ∪
∪ {( , τ), ( , τ), ( , τ), ( , τ) ( , τ) ( , τ)}
Given the two services and shown in Figure 1(b), the composite service S ⟺S is
represented by the LGSPN-Service shown in Figure 3(b).
Parallel (//): Given two services and , the parallel operator builds a composite service
performing the two services ( and ) in parallel. The accomplishment of the resulting service is
achieved when the two services are completed.
Definition 6 The service S //S is defined as S //S = ( , , , , ,
) where:
 = ∪
 = ( , , , , , , , , , , ) where:
= ∪ ∪ { , }, = ∪ ∪ { , } , = ∪ ∪ {( , ), ( , )},
= ∪ ∪ {( , ), ( , ), ( , )}, = ∪ ∪ {( , ), ( , ), ( , )},
= ∪ , = ∪ ∪ {( , ), ( , )| , ∈ ℝ }, = ∪ ,
= ∪ ∪ {( , τ), ( , τ)}
Given the two services and shown in Figure 1(b), the composite service S //S is
represented by the LGSPN-Service shown in Figure 3(c).

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Figure 4. Discriminator Service (a); An abstract exampleof Refinement (b)
Discriminator ((⊡) ≫):The discriminator operator allows tosolicit different services that
perform the same task. The first service that responds activates another service. The other late
responses will be ignored. The discriminator operator allows to benefit from services that respond
in optimal time.
Definition 7 The service (S ⊡ S ) ≫ S is defined as(S ⊡ S ) ≫ S = ( , , ,
, , ) where:
 = ∪ ∪
 = ( , , , , , , , , , , ) where:
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= ∪ ∪ ∪ { , , , }, = ∪ ∪ ∪ { , , , , } ,
= ∪ ∪ ∪ {( , 1), ( , 2), ( , 3), ( , 4), ( , 5), }, = ∪ ∪
∪ {( , ), ( , ), ( , ), ( , ), ( , ), ( , ), ( , )}, = ∪
∪ ∪ {( , ), ( , ), ( , ), ( , ), ( , ), ( , ), ( , )}, = ∪
∪ , = ∪ ∪ ∪ {( , ), ( , ), ( , ), ( , ), ( , )| , ,
, , ∈ ℝ}, = ∪ ∪ , = ∪ ∪ ∪ {( , τ), ( , τ), ( , τ),
( , τ) ( , τ)}
Given the services , and shown in Figure 1(b), the composite service (S ⊡ S ) ≫ S is
represented by the LGSPN-Service shown in Figure 4(a).
Refinement ( ):The refinement operator allows to modify certain service operations and to
replace them by other more detailed operations. This operator allows to change the service
abstraction level from a high level to a lower level more concrete.
Definition 8 The service Re ( , , ) is defined as ( , , ) = ( , , ,
, , ) where:
Figure 4(b) shows an abstract example of a refined service.
, , , , , ∈ ℕ∗
and , , , , , ∈ ℝ.
The proposed algebra verifies the closure property. This latter ensures that the product of any
operation on services is itself a service to which we can apply algebra operators.
4. Related work
During the past years, several approaches for Web service composition have been suggested in
literature. All of these propositions try to provide languages, semantic models, and platforms in
order to propose efficient solutions for this problem.
Composition languages, such as BPEL [9] consist to provide a set of primitives that allows
interaction between services being composed. Regrettably, it comes to textual and executable
languages designed to satisfy the composite web service implementation phase that neglects,
actually, the specification step, which is important, because it facilitates the global

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comprehension of the system, and the development task. Furthermore, since they lack of the
formalism, the formal analysis of the proposed languages is impossible.
Many researches are devoted to the modeling and the composition of web services. Most of these
works provide models expressed in different formalisms.
In [10], Reiko Heckel, and Marc Lohmann have proposed to use the notion of contracts. The last
mentioned refer to graph transformation rules. They are characterized by the assertions
expressing the providers, or the customers’ rights and duties. In addition, this approach uses the
UML notions [11], signatures, and data models to add the behavioral information for the services
web specification. The graph transformation rules have ability, to bring advanced operational
interpretations that cannot be expressed with simple logical expressions,This approach has some
limitations when it comes to a web services complex composition.
Process algebras are a mathematical formalism for describing and studying the concurrent
systems. Several researchers have used different process algebras to specify and compose web
services. For example, Brogi et al. [12] have proposed a formalization technique based on CCS,
for the choreography of web services. In [13], semantics of the orchestration language BPEL is,
this time, specified by using pi-calculus. Nevertheless, this work does not deal with some parts of
BPEL, such as data management; and this is not surprising, because pi-calculus does not allow
data manipulation.
IN [14], the authors have proposed an approach that allows the composite web
servicedevelopment following MDA principles using UML 1.4 as a modeling means. [15] has
used the same idea; this work is based on UML 2.0. However, the authors have pointed out that
the model is not expressive enough. Besides, it is worth to note that UML is a semi-formal
language.
In the field of the formal systems specification, automata are very recognized models. The use of
automata for web services modeling and composition has been suggested by several researchers.
The Columbo model [16], which is based on FSA (Finite State Automata), is one of these
approaches. In [17], Fan et al. have proposed to model the web services using the AFA
(Alternating finite automata). An interaction with the developer to provide, in advance, a detailed
specification of the composite service, is required by these approaches. The use of DFSA
(deterministic finite state automata) is proposed by the authors, in [18], to solve this problem. In
this approach, the developers only define the exactness constraints on the composition. The
behavior of the composite service is automatically synthesized. The use of input output automata
(I/O automata) for modeling the web services composition, has been suggested by Mitra et al., in
[19].
Actually, the disadvantage of using automata is that the competition modeling is not allowed by
their semantics. A solution for this problem has been proposed by Yan and Dague, in [20], the
idea is to model each parallel execution branch by independent automaton, and define events to
realize their interconnection; but, unfortunately, this requires the input and the output state
duplication in each parallel branch.
Concerning Petri-nets, a complete translation of BPEL in Petri-nets has been presented by
Onyang et al., in [21]. Moreover, the ability of the last mentioned in modeling the web services
composition has also been demonstrated by them. Similarly to [7], our approach is a Petri Net
based framework for Web services composition. [7] proposed a Petri Net Algebra. Its model is
enough expressive, but the data types cannot be distinguishable, because an elementary Petri net
model is used. The work of [22] also deals with this problem, by modeling Web services and their
composition using Colored Petri nets [23]. The proposal of [24] is also based on modeling the
process of Web service composition by a kind of Object-Oriented Petri Nets. However, our

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approach is formally defined and is based on a well-founded framework namely LGSPN. In [25]
the authors have proposed an approach for modeling and composition of web services using G-
Nets, which are a kind of high-level Petri nets. The main advantage of our approach compared to
[7], [22],[24] and [25], is the fact that the model used in our work takes into account the time
constraints.LGSPNs are models that can be used for behavioral analyses based on the
classical theory of Petri nets, and also for Performance analyses based on the time
specifications and the probabilistic models.
Ontology-driven approaches for Web services composition like OWL-S [26], SAWSDL [27] and
[28] use terms from preagreed ontologies to declare preconditions and effects of the concerned
services. In the two first works, the inputs and outputs are expressed by concepts, while [28]
describes them in terms of instance-based graph patterns. If these approaches present the
advantage of clearly understanding the meaning of the messages, their main drawback remains
the difficulty to discover the explicit goal of the services. This latter constitutes a key element
when composing by AI planners [29].
5. Conclusion
In this paper, we have presented a simple yet powerful approach, which offers solutions
for both modeling web services and composing them. This approach has the major
advantage of benefiting from the formal aspect of Labeled Generalized Stochastic Petri
Nets (LGSPN). Indeed, modeling based on LGSPN allows the specification and
prototyping of complex Web serviceswith taking into account the time constraints. A
LGSPN-Servicebased algebra for Web service composition is developed. In this vein, we
define the formal semantics of the composition operators by means of LGSPN-Service.
Using this underlying framework provides a rigorous approach to verify the properties
and detect inconsistencies between web services.
In a future work, we plan to extend our approach with advanced operators that can
support more complex Web service combination. Another perspective of our work is to
develop a Java prototype tool implementing the introduced operators. We may also use
reduction techniques to optimize the models before the analysis and the verification of
certain properties by using appropriate tools such as GreatSPN [30].
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