COCOA COnversation-based service COmposition in pervAsive computing environments with QoS support

COCOA:COnversation-based service COmposition

in pervAsive computing environments

with QoS support

Sonia Ben Mokhtar *,Nikolaos Georgantas,Vale

′rie Issarny INRIA Rocquencourt,Domaine de Voluceau,BP 105,78153Le Chesnay Cedex,France

Available online 12March 2007

Abstract

Pervasive computing environments are populated with networked services,i.e.,autonomous software entities,providing a number of

functionalities.One of the most challenging objectives to be achieved within these environments is to assist users in realizing tasks that integrate on the ?y functionalities of the networked services opportunely according to the current pervasive environment.Towards this purpose,we present COCOA,a solution for COnversation-based service COmposition in pervAsive computing environments with QoS support.COCOA provides COCOA-L,an OWL-S based language for the semantic,QoS-aware speci?cation of services and tasks,which further allows the speci?cation of services and tasks conversations.Moreover,COCOA provides two mechanisms:COCOA-SD for the QoS-aware semantic service discovery and COCOA-CI for the QoS-aware integration of service conversations towards the realization of the user task’s conversation.The distinctive feature of COCOA is the ability of integrating on the ?y the conversations of networked services to realize the conversation of the user task,by further meeting the QoS requirements of user tasks.Thereby,COCOA allows the dynamic realization of user tasks according to the speci?cs of the pervasive computing environment in terms of available services and by enforcing valid service consumption.ó2007Elsevier Inc.All rights reserved.

Keywords:Service oriented architectures;Pervasive computing;Semantic web;Dynamic service composition;Work?ow;QoS

1.Introduction

Pervasive computing environments are populated with networked services,i.e.,autonomous software entities,pro-viding a number of functionalities.One of the most challeng-ing objectives to be achieved within these environments is to assist users in realizing tasks that integrate functionalities of the networked services (Sousa and Garlan,2002),so that tasks may be requested anytime,anywhere,and realized on the ?y according to the speci?cs of the pervasive computing environment.To illustrate the kind of situations that we expect to make commonplace through our research,we pres-ent the following scenario (see Fig.1):

‘‘...Today,Jerry is going to travel by train from Paris to London,where he is going to give a talk in a working seminar.At the train station,Jerry has the privilege of waiting in the V.I.P.room.In this room,besides the wonderful French bu?et,a number of digital services are available,among which a streaming service used to stream digital resources on users portable devices,and a large ?at screen that continuously disseminates news.Today,exceptionally,Jerry has arrived early at the train station.When he enters the V.I.P.room,nobody is there.He decides to watch a movie while waiting for his train departure.Jerry uses the e-movie application that he has on his PDA,to which he gives the title of the movie that he wants to watch.This e-movie applica-tion is able to discover video servers as well as display devices available in the reach of the user and to select the most appropriate device.More precisely,if a larger screen than the user’s PDA screen is found in the user’s

0164-1212/$-see front matter ó2007Elsevier Inc.All rights reserved.doi:10.1016/j.jss.2007.03.002

*

Corresponding author.

E-mail addresses:Sonia.Ben_Mokhtar@inria.fr (S.Ben Mokhtar),Nikolaos.Georgantas@inria.fr (N.Georgantas),Valerie.Issarny@inria.fr (V.Issarny).

https://www.wendangku.net/doc/b58207303.html,/locate/jss

Available online at https://www.wendangku.net/doc/b58207303.html,

The Journal of Systems and Software 80(2007)

1941–1955

reach,and if the user’s context allows it(e.g.,nobody else is in the same room),this application displays the movie on that screen.Furthermore,if the user’s context changes(e.g.,the user leaves the room or a person enters in the room),the application is able to transfer the video stream to the user’s PDA.When the train arrives at the station,Jerry gets on the train and continues to watch the movie on his PDA until the train departure...’’.

Hardware resources like displays,and software resources like multimedia streaming servers constitute net-worked capabilities that may conveniently be composed to realize user tasks enabling,for instance,the entertainment of nomadic users.Still,developing pervasive applications as user tasks that bene?t from the open networking envi-ronment raises major software engineering challenges. Functional capabilities accessible in the speci?c networked environment must be abstracted in an adequate way so that applications may specify declaratively required functional capabilities for which concrete instances are to be retrieved on the?y.Furthermore,consumption of networked capabilities shall be achieved in a way that guarantees correctness of the application,both functionally and non-functionally.Another key requirement to indeed enable pervasive applications is for the network to be truly open, with integration of most networked resources,without being unduly selective regarding hosted software and hard-ware platforms.Speci?cally,the pervasive computing envi-ronment shall be able to integrate most networked resources,further allowing the dynamic composition of applications out of capabilities provided by resources, when applications get either requested by users or proac-tively provided by the environment.

The Service-Oriented Architecture(SOA)paradigm, and its associated technologies such as Web services, appears as the right paradigm to engineer pervasive appli-cations.Functional capabilities provided by networked resources may conveniently be abstracted as services.Spe-ci?cally,a pervasive service corresponds to an autonomous networked entity,which provides a set of capabilities.A service capability then corresponds to either a primitive operation of the service or a process composing a number of operations(also referred to as conversation)(Ben Mokhtar et al.,2006a).Consumption of services by client applications(which may themselves realize more complex services available on the network)further requires service clients and providers to agree on both the functional and non-functional semantics of capabilities,so that they can integrate and interact in a way that guarantees dependable service provisioning and consumption.Such an agreement may be carried out at the syntactic level,assuming that clients and providers use a common service description syntax for denoting,besides service access protocols,as well,service semantics.This assumption is actually made by most software platforms for pervasive computing (e.g.,Gaia(Roman et al.,2002),Aura(Sousa and Garlan, 2002),WSAMI(Issarny et al.,2004)).However,such vision based on the strong assumption that service develop-ers and clients describe services with identical terms world-wide,is hardly achievable in open pervasive environments. This raises the issue of syntactic heterogeneity of service descriptions.A promising approach towards addressing syntactic heterogeneity relies on semantic modeling of the services’functional and non-functional features.This con-cept underpins the Semantic Web(Berners-Lee et al., 2001).Combined with Semantic Web technologies,1nota-bly ontologies,for the semantic description of the services’functional and non-functional features,Web services can be automatically and unambiguously discovered and con-sumed in open pervasive computing environments.Specif-ically,ontology-based semantic reasoning enables discovering networked services whose published provided functionalities match a required functionality,even if there is no syntactic conformance between them.A number of research e?orts have been conducted in the area of seman-tic Web service speci?cation,which have led to the develop-ment of various semantic service description languages, e.g.,OWL-S,2WSDL-S,3WSMO,4FLOWS.5Among these e?orts OWL-S,which is based on the Web

Ontology

Fig.1.Scenario.

1Semantic Web:https://www.wendangku.net/doc/b58207303.html,/2001/sw/.

2OWL-S:https://www.wendangku.net/doc/b58207303.html,/services/owl-s.

3WSDL-S:https://www.wendangku.net/doc/b58207303.html,/projects/meteor-s/wsdl-s/.

4WSMO:https://www.wendangku.net/doc/b58207303.html,/.

5FLOWS:https://www.wendangku.net/doc/b58207303.html,/services/swsf/1.0/overview/.

1942S.Ben Mokhtar et al./The Journal of Systems and Software80(2007)1941–1955

Language(OWL),6a W3C recommendation,presents a number of attracting features.Indeed,OWL-S supports the concise speci?cation of service functional capabilities in the service pro?le on the one hand,as well as the detailed speci?cation of the corresponding service conversations on the other hand,which in turn provides a basis for Web ser-vice composition.

Building upon semantic Web services,and particularly OWL-S,we present COCOA,a solution for QoS-aware COnversation-based service COmposition in pervAsive computing environments.COCOA allows the dynamic

realization of user tasks from networked services available in the pervasive computing environment.A preliminary e?ort for de?ning COCOA has been presented in Ben Mokhtar et al.(2006a).In this article,we present the exten-sion of COCOA with support of Quality of Service(QoS). COCOA is part of a larger e?ort on the development of an interoperable middleware for pervasive computing envi-ronments investigated in the IST Amigo project.7COCOA is composed of three major parts.First,COCOA-L,is an OWL-S based language for semantic speci?cation of ser-vices and tasks in pervasive environments.COCOA-L allows the speci?cation of requested and advertised service capabilities,service conversations,as well as service QoS properties.Second,COCOA-SD realizes the discovery and selection of networked services candidate to the com-position.Thanks to the semantic reasoning enabled by the use of ontologies,COCOA-SD enables a thorough matching of service functionalities complemented with QoS-based matching.Finally,COCOA-CI performs dynamic QoS-aware composition of the selected services towards the realization of the target user task.The distinc-tive feature of COCOA-CI is the integration of services modeled as conversations,to realize a user task also mod-eled as a conversation.This provides a mean to deal with the diversity of services in pervasive computing environ-ments.Indeed,as shown in Fig.2,integrating service con-versations for the realization of a user task’s conversation enables the same user task to be performed in di?erent environments by means of several composition schemes (e.g.,by binding to a single service,by composing individ-ual service capabilities,by composing fragments of service conversations or?nally by interleaving fragments of service conversations).Thus,the realization of the task’s conversa-tion is adaptive according to the speci?cs of the environ-ment in terms of available networked services and their provided conversations.Moreover,our approach enforces a valid consumption of the composed services,ensuring that their conversations are ful?lled.

To evaluate our approach,we have implemented a pro-totype of COCOA;experimental results allow us to vali-date the relevance of the employed paradigms in pervasive computing environments.

The remainder of this paper is structured as follows. First,we present related research e?orts in the area of dynamic composition of user tasks in pervasive computing environments,as well as conversation-based service com-position(Section2).Then,we introduce COCOA-L,our language for semantic,QoS-aware speci?cation of services and tasks(Section3).Building on COCOA-L,we present formalisms enabling the realization of COCOA in Section 4,and the mechanisms constituting COCOA in Section5. More speci?cally,the latter concerns COCOA-SD our approach to semantic service discovery,and COCOA-CI our approach to conversation integration.In Section6, we assess our approach based on its performance evalua-tion.Finally,we conclude with a summary of our contribu-tions and future work in Section7.

2.Service composition in pervasive computing environments: state of the art

As introduced in the previous section,a user task is a software application available on the user’s device that is abstractly described in terms of functionalities to be inte-grated.These functionalities have then to be dynamically provided by the environment.Dynamic realization of user tasks is one of the major challenges in mobile environ-ments,as it allows users to perform potentially complex software applications opportunely according to the surrounding environment.A number of research e?orts have been conducted in the area of dynamic realization of user tasks in pervasive computing environments.The Aura project(Sousa and Garlan,2002)de?nes an architec-ture that realizes user tasks in a transparent way.The user tasks de?ned in Aura are composed of abstract services to be found in the environment.Gaia(Roman et al.,2002)is a distributed middleware infrastructure that enables the dynamic deployment and execution of software applica-tions.In this middleware,an application is mapped to available resources of a speci?c active space.This mapping can be either assisted by the user or automatic.Gaia sup-ports the dynamic recon?guration of applications.For instance,it allows changing the composition of an applica-tion dynamically upon a user’s request(e.g.,the user may specify a new device providing a component that should replace a component currently used).Furthermore,Gaia supports the mobility of applications between active

spaces

6OWL:Web Ontology Language.https://www.wendangku.net/doc/b58207303.html,/TR/owl-ref/.

7Amigo:ambient intelligence for the networked home environment.

https://www.wendangku.net/doc/b58207303.html,/euprojects/amigo/.

S.Ben Mokhtar et al./The Journal of Systems and Software80(2007)1941–19551943

by saving the state of the application.Both of the previous platforms introduce advanced middleware to ease the development of pervasive applications composed out of networked resources.However,they are too restrictive regarding the networked resources that may be integrated since resources have to host the speci?c middleware to be known by pervasive applications.Furthermore,both approaches assume framework-dependent XML-based descriptions for services and tasks.In other words,both approaches assume that services and tasks of the pervasive computing environment are aware of the semantics under-

lying the employed XML descriptions.However,in open pervasive environments it is not reasonable to assume that service developers will describe services with identical terms worldwide.This raises the issue of syntactic heterogeneity of service interfaces.Indeed,while building upon service oriented architectures(e.g.,Web services)resolves the het-erogeneity of services in terms of employed technologies, interaction with services is based on the syntactic confor-mance of service interfaces,for which common understand-ing is hardly achievable in open pervasive computing environments.A key requirement for enabling the dynamic realization of user tasks in pervasive environments con-cerns expressing the semantics of services and tasks.

A promising approach addressing the semantic model-ing of information and functionality comes from the Semantic Web paradigm(Berners-Lee et al.,2001).There, information,originally comprehensible only by humans,is enriched with machine-interpretable semantics,so as to allow its automated manipulation.Such semantics of an entity encapsulate the meaning of this entity by reference to a structured vocabulary of terms(ontology)representing a speci?c area of knowledge.Ontology languages support formal description and machine reasoning on ontologies; the Web Ontology Language(OWL)8is a recent recom-mendation by W3C.These notions come from the knowl-edge representation?eld and have been applied and further evolved in the Semantic Web domain.Then,a nat-ural evolution has been the combination of the Semantic Web and Web Services into Semantic Web Services(The DAML Services Coalition,2004).This e?ort aims at the semantic speci?cation of Web services towards automating Web services discovery,invocation,composition and exe-cution monitoring.Hence,a number of research e?orts have been proposed for the semantic speci?cation of Web services.For instance,the latest WSDL(2.0)standard does not only support the use of XML Schema,but also pro-vides standard extensibility features for using,e.g.,classes from OWL ontologies to de?ne Web services input and output data types.A recent proposal for the semantic spec-i?cation of Web services is the Web Services Modeling Ontology(WSMO),which is speci?ed using the Web Ser-vice Modeling Language(WSML).Besides service speci?-cation,this ontology provides support for mediators,which can resolve mismatches between ontologies or ser-vices.METEOR-S(Patil et al.,2004)is another proposal for enhancing Web service descriptions and enabling Web service composition.METEOR-S uses DAML+OIL9 (the direct precursor to OWL)ontologies to add semantics to WSDL and UDDI.

The Web Service Semantics(WSDL-S)proposal,com-ing from the METEOR-S project,also annotates Web ser-vices with semantics,using references to concepts from, e.g.,OWL ontologies,by attaching them to WSDL input, output and fault messages,as well as operations.The First-Order Logic Ontology for Web Services(FLOWS) is a recent proposal for the semantic speci?cation of Web services.It has a well de?ned semantics in?rst-order logic enriched with support of Web based technologies(e.g., URIs,XML).FLOWS encloses parts of other languages and standards(e.g.,WSMO,OWL-S,PSL(ISO18629)) and supports a direct mapping to ROWS,another lan-guage from the same consortium based on logic program-ming(i.e.,rules).OWL-S is a Web service ontology speci?ed in OWL,which is used to describe semantic Web services.A service description in OWL-S is composed of three parts:the service pro?le,the process model and the service grounding(see Fig.3).The service pro?le gives a high level description of a service and its provider.It is gen-erally used for service publication and discovery.The pro-cess model describes the services behavior as a process. This description contains a speci?cation of a set of sub-pro-cesses coordinated by a set of control constructs.These control constructs are:Sequence,Split,Split+Join,Choice, Unordered,If-Then-Else,Repeat-While,and Repeat-Until. The sub-processes can be either composite or https://www.wendangku.net/doc/b58207303.html,-posite processes are decomposable into other atomic or composite processes,while atomic ones correspond to WSDL operations.The service grounding speci?es the information necessary for service invocation,such as com-munication protocols,message formats,serialization, transport and addressing information.The service ground-ing uses WSDL binding information.More precisely,it de?nes mapping rules to link OWL-S atomic processes to WSDL operations.

In the area of ontology-based dynamic service composi-tion in pervasive environments,an e?ort based on

OWL-S

Fig.3.OWL-S top level ontology.

8OWL:https://www.wendangku.net/doc/b58207303.html,/TR/owl-ref/.9DAML+OIL:https://www.wendangku.net/doc/b58207303.html,/TR/daml+oil-reference. 1944S.Ben Mokhtar et al./The Journal of Systems and Software80(2007)1941–1955

has been proposed in Masuoka et al.(2003).In this approach called Task Computing,services of the pervasive computing environment are described as semantic Web ser-vices using OWL-S.Each user of the pervasive computing environment carries a composition tool that discovers on the?y available services in the user’s vicinity and suggests to the user all the possible compositions of these services based on their semantic inputs/outputs.While this approach validates the relevance of semantic Web technol-ogies in pervasive computing environments,it presents some drawbacks.For instance,suggesting to the user all the possible compositions of networked services requires that the user selects the right composition among the sug-gested ones,which can be inconvenient for mobile users of the pervasive computing environment.Indeed,the per-vasive computing environment should minimize the users’distractions by enabling the automatic and transparent deployment and execution of user tasks.Furthermore, the services to be composed are considered as providing a single functionality,while more complex services(e.g., composite services speci?ed with their corresponding con-versation)are not considered for the composition.Such composition,involving services or realizing tasks described with their conversations,identi?ed as conversation-based service composition,allows the realization of more com-plex user tasks.

In the last few years a number of research e?orts have been conducted in the area of conversation-based service composition(Bernstein and Klein,2002;Aggarwal et al., 2004;Majithia et al.,2004;Bansal and Vidal,2003;Brogi et al.,2005).For instance,Bernstein and Klein(2002)pro-pose to describe services as processes,and de?ne a request language named PQL(Process Query Language).This lan-guage allows?nding in a process database those processes that contain a fragment that corresponds to the request. While this approach proposes a process query language to search for a process,it does not handle process integra-tion.Thus,the authors implicitly assume that the user’s request is quite simple and can be performed by a single process.On the contrary,in our approach a composition e?ort is made to reconstruct a task conversation by inte-grating services conversations.

Aggarwal et al.propose to describe a task conversation as a BPEL4WS10work?ow(Aggarwal et al.,2004).This description may contain both references to known services (static links)and abstract descriptions of services to be inte-grated(service templates).At execution time,services that match the service templates are discovered,and the task’s work?ow is carried out by invoking the selected services. This approach proposes a composition scheme,in which a set of services are integrated to reconstruct a task’s con-versation.However,the services being integrated are rather simple.Indeed,each service is described at the interface level without describing the service conversation.On the contrary,we consider services as entities that can behave in a complex manner,and we try to compose these services to realize the user task’s conversation.

Another conversation-based matching algorithm is pro-posed by Majithia et al.(2004).In this approach,the user’s request is speci?ed at the interface level and is mapped to a work?ow.Then,service instances that match the ones described in the work?ow,in terms of inputs,outputs, pre-conditions and e?ects,are discovered in the network, and a concrete work?ow description is constituted.As for the previous approaches,the service composition scheme that is proposed does not involve any conversation integration,as the Web services are only described at the interface-level.

The work proposed by Bansal and Vidal(2003)uses the OWL-S process model to match services.In their approach,the authors consider a user request in the form of required inputs/outputs,and assume a repository of OWL-S Web services.Then,they propose a matching algo-rithm that checks whether there is a process model in the repository that meets the desired inputs/outputs.Brogi et al.(2005)have proposed an enhancement of this last algorithm by performing a composition of services’process models to respond to inputs/outputs of the user’s request. This last e?ort is close to our work,as an e?ort of integrat-ing conversations is investigated.However,some di?er-ences remain.The main di?erence is that the authors consider that the user request can be expressed in the form of a list of inputs/outputs.While this is an interesting assumption,this implicitly prevents the user from perform-ing complex conversations.Indeed,the algorithm com-poses in a pipe and?lter like-way,atomic processes that are compatible in terms of provided outputs and requested inputs(signatures).While this strongly guarantees that the composed services will be able to exchange information,it weakly guarantees that the resulting composition will pro-vide the user with the expected semantics.On the contrary, we consider that the user’s request is expressed as a conver-sation,which guarantees that the resulting composition will indeed meet the user task’s expected behavior.

The QoS-aware dynamic realization of tasks in perva-sive computing environments through the integration of service conversations calls for a language that allows the semantic-aware description of services and of tasks’func-tional and non-functional capabilities,as well as of ser-vices’and tasks’conversations.For this purpose,we present in the following section COCOA-L,a language for speci?cation of services and tasks of the pervasive environment.

3.COCOA-L:an OWL-S based service and task description language

We describe herein COCOA-L,an OWL-S based lan-guage for the speci?cation of networked services and user tasks in pervasive environments.This language extends

10BPEL4WS:https://www.wendangku.net/doc/b58207303.html,/developerworks/library/

ws-bpel/.

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OWL-S in order to?t the requirements of service composi-tion in pervasive computing environments.Speci?cally, COCOA-L allows the speci?cation of:

(1)Services’and tasks’advertised and requested func-

tional capabilities;

(2)Services’and tasks’conversations for modeling their

behavior;and

(3)Services’and tasks’QoS properties.

The UML diagram depicted in Fig.4represents the main conceptual elements of COCOA-L with respect to(1),(2) and(3).These elements are further detailed in the following three sections.Note that in this diagram,colored boxes are those corresponding to reused OWL-S elements.

3.1.Requested and advertised capabilities

At the heart of COCOA-L,we distinguish the notion of capability.A capability characterizes a functionality that might be requested or advertised by a service/task.A capa-bility is realized by the invocation of a set of operations,i.e., a sequence of messages exchanged between a client and a service provider(e.g.,WSDL operations).A requested capa-bility has a set of provided inputs,a required category,and a set of required outputs and QoS properties;while an adver-tised capability has a set of required inputs,a provided cat-egory,and a set of provided outputs and QoS properties.

In COCOA-L,both user tasks and services are speci?ed with a conversation,which comprises respectively requested and advertised capabilities.When a user task is being per-formed,its requested capabilities have to be bound to advertised capabilities of networked services.

3.2.Service conversation speci?cation

A conversation represents the coordination of a set of capabilities by control constructs(e.g.,Sequence,Parallel,Choice constructs).In COCOA-L,we use the OWL-S con-trol constructs for coordinating capabilities of services and tasks.Due to their involvement in a conversation,capabil-ities have data and control dependencies between each other.Control dependencies are those due to the structure of the conversation.Speci?cally,two capabilities C1and C2 are said to have a control dependency if C1is prior to C2in the conversation,and in order to enforce a valid service/ task consumption C1must be performed before C2when the service/task is being performed.Nevertheless,when realizing user tasks,the interleaving of multiple service con-versations is supported as long as the services control dependencies are ful?lled.For instance,if the user task conversation is a sequence of the four capabilities Sequen-ce(C1,C2,C3,C4)and the two services to be composed S1 and S2have respectively the two following conversations: Sequence(C1,C3)and Sequence(C2,C4),a composition that interleaves S1and S2conversations,while meeting S1and S2control dependencies,is given as follows:

SequenceeS1áC1;S2áC2;S1áC3;S2áC4T:

A data dependency between two capabilities C1and C2 is speci?ed when data produced by C1must be consumed by C2and only by C2.When a data dependency is speci?ed in a user task conversation,this means that the correspond-ing two capabilities must be provided by the same service. For instance,when realizing a user task comprising a book-ing and payment capabilities for a hotel room,one can imagine that it is not possible to use the booking capability of a hotel reservation service and the payment capability of another hotel reservation service.In the example of Fig.5, a data dependency is speci?ed between the capabilities Browse and Get Stream of the e-movie application,which means that these two capabilities must be provided by the same networked service.If a data dependency is speci-?ed in a service conversation,this means that the corre-sponding capabilities must be performed in sequence without interleaving with other capabilities outside the ser-vice conversation.

COCOA-L further supports the speci?cation of data ?ow between capabilities.Speci?cally,data?ow speci?es which output data produced by a capability may be con-sumed by another capability.Data?ow speci?cation is nevertheless di?erent from data dependencies in the fact that it does not drive the service selection process.For instance,if the user task contains the speci?cation of a data dependency between two capabilities,it will drive the selec-tion of services that provide both capabilities in the same conversation,while specifying a data?ow relation does not lead to any constraint in service selection.Indeed,the selection of two capabilities that belong to two di?erent services may be performed,as long as the selected capabil-ities are compatible in terms of inputs/outputs to be exchanged with respect to the data?ow speci?cation.

Our objective is to realize user tasks based on their con-versation speci?cation through the integration of services also speci?ed with their conversation.This

integration Fig.4.COCOA-L.

1946S.Ben Mokhtar et al./The Journal of Systems and Software80(2007)1941–1955

has to ful?ll both data and control dependencies of user tasks and services.

3.3.Service QoS speci?cation and measurement

3.3.1.QoS speci?cation

QoS speci?cation associated with the dynamic composi-tion of user tasks is concerned with capturing the user tasks QoS requirements as well as services QoS properties.QoS speci?cation should:(1)allow the description of both quantitative(e.g.,service latency)and qualitative(e.g., CPU scheduling mechanism)QoS attributes;and(2)be declarative in nature,that is,specify only what is requested, but not how the requirements should be implemented by services(Aurrecoechea et al.,1998).

In the following,QoS category refers to a speci?c non-functional property of a service that we are interested in (e.g.,performance).Every category consists of one or more dimensions,each representing one attribute of the category. For instance,latency de?nes a dimension of the performance category.Quantitative dimensions in QoS speci?cation,also referred to as metrics,measure speci?c quanti?able attri-butes of the service.Qualitative dimensions,referred to as policies,dictate the behavior of the services.These dimen-sions are described in COCOA-L with references to ontol-ogy concepts.Sabata et al.further classify the metrics into categories of performance,security levels,and relative impor-tance.Policies are divided into categories of management and level of service(Sabata et al.,1997).

Based on the aforementioned work,and the work intro-duced in Ben Mokhtar et al.(2005),we introduce a base QoS speci?cation of services depicted in the UML diagram of Fig.6,which is adapted to pervasive environments.Spe-ci?cally,we notice that although more QoS parameters yield more detailed description,the gain has to be put up against the increased https://www.wendangku.net/doc/b58207303.html,ually,a small number of param-eters(i.e.,65)is su?cient to capture the dominant QoS properties of a system(Dijk et al.,2000).Along with the fac-tor of limited resources on mobile devices,we only take into account the most dominant and descriptive dimensions in our base QoS speci?cation,instead of trying to incorporate every possible applicable dimension.However,it can be eas-ily extended with more dimensions,if requested by speci?c services or tasks,by supporting the new dimensions in a way similar to the ones discussed in this section.

In the latter diagram,dark colored boxes represent qual-itative dimensions,whereas light colored boxes represent quantitative ones.A QoS Property,is described based on QoS dimensions and expressed as a boolean expression using the following operators:and,or,not,equal,not-equal, is-a,is-exactly-a,is-not-a,more-than,less-than,max-value-of,min-value-of.The operators is-a,is-exactly-a and is-not-a are used to compare qualitative properties,while equal,not-equal,more-than,less-than,max-value-of,min-value-of operators are used to compare quantitative prop-erties.Finally,the and,or and not operators are used to de?ne composite properties.

According to our service model depicted in Fig.4,a user task has two kinds of required QoS properties:QoS prop-erties speci?ed at the level of capabilities expressing local QoS requirements,and QoS properties speci?ed at the level of the whole task expressing global QoS requirements. Local QoS requirements have to be satis?ed by individual advertised capabilities of services,whereas global QoS requirements has to be satis?ed by the resulting service composition.The mechanisms used to check the ful?llment of local and global QoS properties of user tasks are further detailed in Sections5.1and5.2,respectively.

3.3.2.Measurement of quantitative QoS dimensions

The speci?cation of quantitative QoS dimensions in service requests and advertisements requires providing dimension measuring as accurate as possible.Service-level dimensions can be measured easily(e.g.,o?-line measure-ments using available quality analysis tools).Resource-related measures for the services are also easy to obtain after service execution,using available utilities(e.g.,path-char11for bandwidth measurement).However,providing accurate metrics measures for the selection of services prior to their execution requires special care,since this relates to predicting the service’s resource consumption.The predic-tion of service metrics can be carried out based on histories (Flinn et al.,2002;Narayanan and Satyanarayanan,

2003;

11https://www.wendangku.net/doc/b58207303.html,/tools/utilities/others/pathchar.

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Gurun et al.,2004),which has been proved to be accurate and e?cient (Gurun et al.,2004).

In our case,while evaluating the QoS of a service com-position,we provide two estimations for each QoS dimen-sion:(1)a history-based,probabilistic estimation;and (2)a pessimistic estimation.The former corresponds to an aver-age estimation,while the latter corresponds to a worst case estimation.Actually,we consider both the previous estima-tions,which depend on the user’s task requirement (e.g.,deterministic or probabilistic)in the user’s request.For example,if the user demands a deterministic QoS,our approach compares the requested QoS with the pessimistic estimation of the composite service.If the user requires an average QoS,the latter is compared against the probabilis-tic estimation.Further details about how we perform these estimations are given in Section 4.2.Moreover,we use relative importance to characterize both the users’prefer-ences among the various QoS dimensions and the criticality of the hosts’resources.Further details about the use of relative importance among QoS dimensions are given in Section 5.2.

4.Formalisms for QoS-aware dynamic service composition In this section we introduce two formalisms enabling the integration of services’conversations for realizing user tasks with support of QoS.

4.1.Modeling service conversations as FSA

In order to ease service composition by enforcing control and data dependencies of services/tasks,we propose to model services and tasks conversations using ?nite state automata.Other approaches to formalizing Web services conversations and composition have been proposed in the literature based on Petri nets (van der Aalst and ter Hofst-ede,2004),process algebras (Koshkina and van Breugel,2003)or ?nite state machines (Foster et al.,2003).Fig.7describes the mapping rules that we have de?ned for trans-lating an OWL-S process model to a ?nite state automaton.In this model,automata symbols correspond to capabilities described using COCOA-L.The initial state corresponds to the beginning of the conversation,and ?nal states corre-spond to the end of a client/service interaction.Each con-trol construct involved in a conversation is mapped to an automaton using the rules depicted in Fig.7.Then,these automata are linked together in order to build a global automaton.Further details about modeling OWL-S pro-cesses as automata can be found in Ben Mokhtar et al.(2005).Fig.8shows the automaton representing the e-movie application .Both user tasks and networked services are modeled as ?nite state automata.However,the user task’s automaton is enriched with additional information in some of its transitions,i.e.,the probability for this transition to be selected.More precisely,a probability value is introduced

in

Fig.6.QoS speci?cation.

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the case of a Repeat-While,Repeat-Until and Choice con-structs.For the?rst two constructs(loops),the information added is the probability for the corresponding process to be executed once again.In the case of the Choice control con-struct,a probability is attached to each possible choice of this construct.This information is necessary to calculate a probabilistic QoS estimation of a composition,as further discussed in the following section.For instance,if a compo-sition involves a loop,the QoS of this composition depends on how many times the user will execute this loop.All these probabilities are evaluated based on histories and are updated each time the user task is executed.In addition to these probabilities,some other information is needed to estimate the worst case value of QoS parameters.This infor-mation is attached to each loop construct in the task’s pro-cess,and gives the maximum number of times the loop can be carried out during the execution of a user task.

4.2.Evaluating the QoS of composed User Tasks

In our approach,as the task is abstract,i.e.,do not refer to speci?c services,we need to extract the QoS formulae corresponding to each QoS metric.These formulae are extracted in advance and stored with the task’s description. Then,during the composition,each time an element is being composed,these formulae are used to check the ful-?llment of the task’s QoS requirements.A number of research e?orts propose reduction rules to compute the QoS of a work?ow(Cardoso et al.,2004;Menasce, 2004).We use the model proposed by Cardoso et al. (2004)to extract the formula of each QoS dimension,cor-responding to the task’s automaton structure.In this approach,a mathematical model is used to compute QoS for a given work?ow process.More precisely,an algorithm repeatedly applies a set of reduction rules to a work?ow until only one atomic node remains.This remaining node contains the QoS formula for each considered metric,cor-responding to the work?ow under analysis.The algorithm uses a set of six reduction rules:(1)sequential,(2)parallel, (3)conditional,(4)fault-tolerant,(5)loop and(6)network. However,as our automata model is an abstraction of the OWL-S work?ow constructs,we only need to keep the reduction rules for sequential,conditional,and loops systems.

As introduced earlier,we provide two estimations for each QoS dimension:(1)a history-based probabilistic esti-mation and(2)a pessimistic estimation.Fig.9and Tables1 and2show how we perform these estimations.Fig.9 describes the reduction rules to be applied for sequence, choice and both simple and dual loop constructs.In this ?gure capabilities represented on each transition(named o i)provides some QoS attributes(e.g.,Availability(noted a i),Latency(noted l i),Cost12(noted c i)).Besides these attributes,some capabilities,i.e.those involved in the choice and loops constructs,have additional information, i.e.,the probability to be selected(p i).These probabilities are only used in the case of a probabilistic average estima-

12In the following we refer cost to any cost-related dimension,e.g.,CPU

load,memory.

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tion of QoS.The formulae to be applied in this case are described in Table 1.Note that in this Table,for each loop case,the probabilities p i described in Fig.9,are changing to

p 0i after reduction,where:p 0i ?p i

.On the other hand,eval-uating a worst case estimation of QoS requires the use of the above reduction rules,by applying the formulae described in Table 2.In this case another information is required for both loop cases,which is the maximum num-ber of times a loop can be executed,as described earlier.This information is represented by N in Table 2.

We focus on the QoS of a service composition with respect to the three dimensions:availability,latency and cost,because they are considered as important QoS dimen-sions of user tasks (e.g.,Cardoso et al.,2004)and other quantitative dimensions can be calculated in a similar way.For qualitative dimensions,their evaluation is trivial since it only needs to ensure that the policy of each com-posed service is no weaker than the user’s request.This is done by reasoning on the semantic concepts describing the required policies and the provided ones.

Having these two formalisms introduced,we present in the following two sections the two mechanisms constituting COCOA,i.e.,QoS-aware service discovery (COCOA-SD)in Section 5.1,and QoS-aware conversation integration (COCOA-CI)in Section 5.2.

5.Mechanisms for QoS-aware dynamic service composition 5.1.QoS-aware service discovery:COCOA-SD

Service discovery allows ?nding in the pervasive envi-ronment,at the speci?c time and place,service advertised capabilities that match service requested capabilities towards the realization of user tasks.Service discovery decomposes into service matching and service selection as described below.

5.1.1.Service matching

Service matching allows identifying services that provide semantically equivalent capabilities with those of the user

task’s conversation.Furthermore,these capabilities should ful?ll the QoS properties required in the task’s requested capabilities.We use the matching relation Match (Adv ,Req )to match an advertised capability Adv against a requested capability Req .This relation extends the relation de?ned in Ben Mokhtar et al.(2006b)with the matching of QoS properties.Speci?cally,the Match relation is de?ned using the function distance (concept 1,concept 2),hereafter denoted by d (concept 1,concept 2),which gives the semantic distance between two concepts,concept 1and concept 2,as given in the classi?ed ontology to which the concepts belong.Pre-cisely,if concept 1does not subsume 13concept 2in the ontol-ogy to which they belong to,the distance between the two concepts does not have a numeric value,i.e.,d (con-cept 1,concept 2)=NULL .Otherwise,i.e.,if concept 1sub-sumes concept 2,the distance takes as value the number of levels that separate concept 1from concept 2in the ontology hierarchy obtained after ontology classi?cation.In this relation,we consider the case where concept 1is subsumed by concept 2as a mismatch and we assign the value NULL to the relation d because such matching implies that a client may be provided with an advertised capability that is more speci?c than the requested capability,which may lead to a malfunction of the advertised capability.For instance,if the advertised capability translates only Latin languages into other Latin languages,and the client provides in its requested capability the concept Language as input,which subsumes both Greek and Latin languages,the advertised capability will not work if the client invokes the corre-sponding service with a text in Greek as input.Moreover,as we aim at the automatic realization of user tasks we opt for the selection of only capabilities that are equivalent or more generic than the requested capabilities,thus avoid-ing the risk of malfunctioning capabilities.

Formally,let the advertised capability Adv be de?ned by the set of required inputs Adv .In ,a set of provided outputs Adv .Out ,a provided category Adv .Cat ,and a set of pro-vided QoS properties Adv .P .On the other hand,let the requested capability Req be de?ned by a set of provided inputs Req .In ,a set of required outputs Req .Out ,a required category Req .Cat and a set of required QoS properties Req .P .The relation Match is then de?ned as:

Match eAdv ;Req T?8in 02Adv :In ;9in 2Req :In :d ein ;in 0TP 0and 8out 02Req :Out ;9out 2Adv :Out :d eout ;out 0TP 0and d eAdv :Cat ;Req :Cat TP 0

8p 02Req :P ;9p 2Adv :P :ep )p 0T

From the above,the relation Match (Adv ,Req )holds if and only if all the required inputs of Adv are matched with in-puts provided by Req ;all the required outputs of Req are matched with outputs provided by Adv ;the category re-quired by Req is matched with the category provided by

Table 1

History-based probabilistic average QoS evaluation

Seq

Choice Simple loop

Dual loop

Availability a 1*a 2P a i p i e1àp T?a o o e1àp T?a o o o 0

Latency l 1+l 2P l i p i l o 1àp l o tl o 0àe1àpl o 0T

1àp Cost

c 1+c 2

P c i p i

c o 1àp

c o tc o 0àe1àp Tc o 0

1àp

Table 2

Pessimistic QoS evaluation

Seq

Choice Simple loop Dual loop

Availability a 1*a 2Min (a i )N *a o *Min (a i )N *a o *a o 0*Min (a i )Latency l 1+l 2Max (l i )N *l o +Max (l i )N *(l o +l o 0)+Max (l i )Cost

c 1+c 2

Max (c i )

N *c o +Max (c i )

N *(c o +c o 0)+Max (c i )

13

Subsumption means the fact to incorporate something under a more general category.

1950S.Ben Mokhtar et al./The Journal of Systems and Software 80(2007)1941–1955

Adv and all the required properties of Req are matched with properties provided by Adv.

5.1.2.Service selection

Service selection allows identifying which services from those that o?er semantically equivalent capabilities to the capabilities of the user task are potentially useful for the composition.The selection of services is based on the con-trol dependencies that are inherent to their conversation speci?cation.For instance,a service that provides a seman-tically equivalent capability to one of the requested capa-bilities of the user task,could not be useful for the composition if the latter capability has data or control dependencies with capabilities that are not requested at all in the user task.To perform this selection we use regular expressions.Speci?cally,we extract from the task automa-ton the regular expression that represents the language gen-erated by this automaton.For each term of this regular expression,which corresponds to a capability from the task description,we introduce the quanti?er?that indicates that there is0or1occurrence of this term.For example,the regular expression extracted for the automaton of the e-movie application presented in Fig.8is given by:

eBrowseT?eSearchDisplayT?eGetStreamT?eGetContextT?

eLocalDisplayT?jeSearchDisplayT?eGetStreamT?eGetContextT?eLocalDisplayT?jeLocalDisplayT?

Let’s note by L the language generated by the extracted regular expression and by L1,L2,...,L n the languages gen-erated by the automata of the pre-selected services S1,S2,...,S n,respectively.COCOA-SD selects all the ser-vices S i such that L\L i5;.For example,a service that provides a sequence of capabilities that match semantically the capabilities Browse and GetStream of the user task,is selected.

This allows the selection of services that meet the control dependencies of the user task by enabling the potential interleaving of their conversations.Furthermore,if a data dependency is speci?ed between two capabilities of the user task,only services that provide both these capabilities in their conversation are kept from the previously selected services.

Service selection is also based on QoS speci?cations. Particularly,if local QoS requirements are speci?ed in some capabilities of the user task,service capabilities that do not ful?ll the latter requirements are not selected for the composition.

5.2.QoS-aware conversation integration:COCOA-CI

Once semantic-aware service discovery is achieved,the next step towards dynamic composition of user tasks,is the integration of the conversations of the selected services. COCOA-CI integrates the conversations of services selected using COCOA-SD,to realize the conversation of the target user task.Moreover,COCOA-CI supports inter-leaving of these conversations.COCOA-CI integrates the conversations of discovered services to realize the user task, based on associated state automata.

COCOA-CI?rst integrates all the automata of selected services in one global automaton.The global automaton contains a new start state and empty transitions that con-nect this state with the start states of all selected automata. The automaton also contains other empty transitions that connect the?nal states of each selected automaton with the new start state.Consider the automaton representing the conversation of the target user task depicted in Fig.10,left higher corner,and the automata representing the conversations of the selected services,Fig.10,right lower corner.In this?gure,all the automata of the selected services are connected in a global automaton,in which all the added transitions are represented with dashed lines.

The next step of COCOA-CI is to parse each state of the task’s automaton starting with its start state,and following its transitions.Simultaneously,a parsing of the global automaton is carried out in order to?nd for each state of the task’s automaton a state of the global automaton that can simulate it,i.e.,a task’s automaton state is simu-lated by a global automaton state when for each incoming symbol14of the former there is at least one semantically equivalent15incoming symbol of the latter.For example, in Fig.10,the state t1of the task’s automaton can be sim-ulated by the initial state of the global automaton because the set of incoming symbols of t1,is a subset of the set of incoming symbols of the global automaton initial state.

COCOA-CI allows?nding service compositions with possible interleaving of conversations of the involved ser-vices.Indeed,this is done by managing service sessions.

A service session characterizes the execution state of a ser-vice conversation.A session is opened when a service con-versation starts and ends when this conversation?nishes. Several sessions with several networked services can be opened at the same time.This allows interleaving the inter-actions with distinct networked services.Indeed,a session opened with a service A can remain opened(temporary inactive)during the interaction of the client with another service B.An example of managing sessions is given in Step (1)of the composition.In this step,the capability Browse of the task’s automaton has been matched against the capabil-ity Browse of the global automaton.The next step is to?nd the capability Search Display of the task’s automaton(Step (2)).However,this capability is not available in the Video Streaming Service.This leads to open another session with the Display Service as this service provides the sought capa-bility.In Step(3)after matching the capability Search Dis-play,the capability Get Stream is sought.A semantically equivalent capability,i.e.,the Send Stream capability,is 14Incoming symbols of a state correspond to the labels of the next transitions of this state.

15We recall that equivalence relationship between capabilities is a semantic equivalence that have already been checked by COCOA-SD.

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accessible in the Video Streaming Service from the previ-ously opened session.

An important condition that has to be observed when managing sessions is that each opened session must be closed,i.e.,it must arrive to a?nal state of the service automaton.During the composition process,various paths in the global automaton,which represent intermediate com-positions,are investigated.Some of these paths will be rejected during the composition while some others will be kept(e.g.,if a path involves a service in which a session has been opened but never closed,this path will be rejected).

In addition to checking for each state the equivalence between incoming capabilities,a veri?cation of the confor-mance to the QoS constraints of the user task is performed. This is done by using the QoS formulae that have been extracted from the task’s automaton structure as described in Section4.2.Thus,we start with the QoS formula for each QoS dimension,in which we initially assume that all capabilities will provide the best value of the considered QoS dimension(for example,latency=0,availability=1). Then,each time we examine a service capability,we replace the corresponding best value in the formula of the consid-ered dimension,with the real QoS value of the capability. This allows evaluating at each step of the integration the values of all QoS dimensions in the case that the current capability is selected.These values are then compared to the corresponding values required by the user task,and if the constraints are not met,the path in the global autom-aton that includes this capability is rejected.

COCOA-CI gives a set of sub-automata from the global automaton that conforms to the task’s automaton struc-ture(two sub-automata are depicted in the left lower cor-ner of Fig.10).Each of these automata is a composition of networked services that conforms to the conversation of the target user task,further enforcing valid service

consumption.

1952S.Ben Mokhtar et al./The Journal of Systems and Software80(2007)1941–1955

Once the set of possible compositions is given(See Fig.10where two compositions are given by COCOA-CI),a last stage is to choose the best among resulting com-positions,on the basis of provided QoS.However,since di?erent dimensions are in di?erent units,data normaliza-tion is needed.In our case,we apply standard deviation normalization on the various dimensions as in Issarny and Liu(2004):

d0ec iT?

2ifedec iTàmedT>2?dedTT

0ifedec iTàmedT<à2?dedTT

dec iTàmedT

2?dedT

t1otherwise

8

><

>:

e1T

where d(c i)is the value of dimension d for the service com-position c i,and m(d)and d(d)are the mean value and stan-dard deviation for dimension d,respectively.Note that for QoS parameters that are stronger with smaller values(e.g., latency),d0(c i)is further transformed by d00(c i)=2àd0(c i), so that stronger values are normalized to greater values.

With every dimension normalized,every service compo-sition is evaluated based on a bene?t function like in Issarny and Liu(2004):

Overall Benefit?

X n

i?1

edec iT?w iT=Service Composition Cost

e2Twhere w i is the relative importance of the considered dimension.

Using the service composition that has been selected,the conversation description of the user task is complemented with information coming from the composed services.Spe-ci?cally,each capability of the user task is replaced with the corresponding capability of the networked services.This capability may correspond to either one single or a sequence of client/service interactions.Furthermore,a grounding description for the user task,which contains the binding information of the composed services is generated.

The complemented task’s description and the generated grounding are sent to an execution engine that performs the user task by invoking the appropriate networked services.

6.Prototype implementation and performance evaluation

COCOA decomposes into two main mechanisms, COCOA-SD for discovering component services and COCOA-CI for integrating the conversations of selected services.COCOA-SD relies on semantic reasoning on ontologies used to infer relations between semantic descrip-tions,which we have identi?ed as a costly mechanism(Ben Mokhtar et al.,2006c).Nevertheless,semantic discovery of service capabilities can be performed e?ciently in pervasive computing environments upon the deployment of appro-priate solutions.Indeed,in Ben Mokhtar et al.(2006b) we present an e?cient semantic service discovery protocol for pervasive computing environments.Results show that rich,semantic service discovery can be performed with response times comparable to the syntactic WSDL-based service discovery.Furthermore,we de?ne mechanisms for structuring service repositories based on the semantic spec-i?cation of services,which increases the scalability of our protocol.Further details about e?cient semantic service discovery in pervasive computing environments can be found in Ben Mokhtar et al.(2006b).

In this article we are primarily interested in evaluating the performance of COCOA-CI,which is at the heart of the composition process,as well as the impact of support-ing QoS awareness.

We have implemented COCOA-CI in Java,on a Linux platform running on a laptop with an Intel Pentium4, 2.80GHz CPU and512MB of memory.The performance of COCOA-CI is proportional to the complexity of the task and services’conversations.Speci?cally,the response time of the algorithm is proportional to the number of possible (intermediate)composition paths investigated during the execution of the algorithm.There are two main factors contributing to the increase of the intermediate composi-tion paths:(1)the number of semantically equivalent capa-bilities provided by networked services;(2)the number of capabilities requested in the task’s conversation.We have carried out two experiments,each evaluating the impact of each factor on the performance of COCOA-CI.In both experiments,each value is calculated from an average of10 runs.

Fig.11considers the?rst factor.In this?gure,the num-ber of capabilities provided by networked services is increasing from10to100capabilities that are semantically equivalent.We compare the performance of COCOA-CI with the XML parsing of the services and task descriptions, which is inherent to the use of Web services and semantic Web technologies.The resulting curves show that the cost of our algorithm is negligible compared to the XML pars-ing time.Fig.12considers the second factor.In this?gure,

S.Ben Mokhtar et al./The Journal of Systems and Software80(2007)1941–19551953

the number of capabilities provided by the networked ser-vices is?xed to the worst case coming from the previous experiment,i.e.,100semantically equivalent capabilities, while the number of capabilities requested in the task’s conversation is increasing from1to20.The experiment that is depicted in this?gure corresponds to the compari-son of the performance of COCOA-CI with the XML pars-ing of the services and the task conversation descriptions. The?gure shows an extreme scenario for our algorithm, as each capability requested in the task’s conversation is matched against100capabilities,and the resulting number of possible compositions is equal to:100nb in each case, where nb is the number of capabilities requested in the task’s conversation.We can see that for a number of pos-sible compositions less than10010,our algorithm takes less time than the XML parsing time.In realistic cases,both the user task and networked services will contain various capa-bilities organized using various work?ow constructs,thus leading to the decrease of possible resulting compositions. Consequently,the response time will be reasonable for the pervasive computing environment.Indeed,we have applied our algorithm in a real case example in which the task’s conversation contains twenty requested capabilities and the selected services provide thirty capabilities,includ-ing various control constructs(e.g.sequence,choice,loop). In spite of the large number of capabilities requested in the task’s conversation,the algorithm spent only32millisec-onds to?nd the two resulting compositions among36 intermediate compositions,against152milliseconds for the XML parsing time.

Fig.12shows also another important result,which is the impact of introducing QoS in our integration algorithm. This impact is amounts to a small increase in the XML parsing time,which is due to the addition of XML tags for describing QoS,while at the same time to a consider-able decrease of the execution time of our algorithm.This is attributed to the rejection of a number of paths that do not ful?ll the QoS requirements of the user task during the integration.7.Conclusion

The pervasive computing vision is increasingly enabled by the large success of wireless networks and devices.In pervasive environments,heterogeneous software and hard-ware resources may be discovered and integrated transpar-ently towards assisting the performance of users’daily tasks.Building upon the service oriented architecture par-adigm and particularly Web services allows having a homogeneous view of the heterogeneous services populat-ing pervasive environments,as services have standard descriptions and communicate using standard protocols. However,realizing such a vision still requires dealing with the syntactic heterogeneity of service descriptions.Most existing solutions to dynamic composition of networked services in pervasive environments poorly deal with such heterogeneity,since they assume that components being integrated have been developed to conform syntactically in terms of interfaces.

Building upon semantic Web services,we presented in this article COCOA,our solution to dynamic service com-position in pervasive computing environments.COCOA presents a number of attractive features.Indeed,COCOA enables the integration of services having a complex behav-ior for the realization of user tasks that also have complex behaviors.Speci?cally,the realization of the user task varies each time a user task is performed according to the speci?cs of services available in the current pervasive environment. This realization may vary from the integration of individual service capabilities,to the interleaving of potentially com-plex service conversations.Furthermore,COCOA allows meeting QoS requirements of user tasks.

For the QoS-aware dynamic realization of tasks,we?rst presented COCOA-L,an OWL-S based language enabling the speci?cation of service advertised and requested capa-bilities,service conversations,as well as the speci?cation of QoS properties.Then,we presented COCOA-SD,which enables QoS-aware semantic service discovery and COCOA-CI,for the QoS-aware dynamic integration of the selected service conversations.

To perform such a composition,COCOA introduces an abstraction of OWL-S based conversations as?nite state automata.This translates the di?cult issue of con-versation integration to an automata analysis problem by further enabling the assessment of services and tasks data and control dependencies.Furthermore,for enabling QoS-awareness,COCOA-L allows the speci?cation of both local and global QoS requirements of user tasks. Task’s local QoS requirements are those related to partic-ular requested capabilities of the user task,they are checked by COCOA-SD when selecting service advertised capabilities that semantically match requested capabilities of the user task.On the other hand,global QoS require-ments are checked by COCOA-CI when integrating ser-vice conversations and require the aggregation of QoS properties coming from the multiple advertised capabili-ties to be integrated.

1954S.Ben Mokhtar et al./The Journal of Systems and Software80(2007)1941–1955

We further presented in this article a prototype imple-mentation and evaluation of COCOA.In this article,we have been primarily interested in evaluating the perfor-mance of COCOA-CI and the impact of introducing QoS-awareness in the composition process.Indeed,a preli-minary solution for e?cient semantic service discovery in pervasive environment,has previously been introduced in Ben Mokhtar et al.(2006b).For evaluating a prototype implementation of COCOA-CI,we have compared its response time against the time spent for the XML parsing of services and task descriptions,which is inherent to the use of Web services and semantic Web technologies. Results show that in more realistic cases,COCOA over-head is negligible compared to XML parsing.We have fur-ther done experiments for evaluating the impact of introducing QoS-awareness in COCOA.Results show the introduction of QoS constraints improves the performance of COCOA-CI.Our ongoing research e?orts include the deployment of COCOA-CI on top of an existing semantic service discovery protocol for pervasive environments(e.g., Ben Mokhtar et al.,2006b),such that the composition of user tasks can be performed transparently and in a distrib-uted manner by a set of collaborating service directories of the pervasive computing environment.

References

Aggarwal,Rohit,Verma,Kunal,Miller,John,Milnor,Willie,2004.

Dynamic web service composition in meteor-s.Technical report, LSDIS Lab,Computer Science Dept.,UGA.

Aurrecoechea, C.,Campell, A.T.,Hauw,L.,1998.A survey of QoS architectures.ACM/Springer Verlag Multimedia Systems Journal, Special Issue on QoS Architecture.3(6)138–151.

Bansal,Sharad,Vidal,Jose M.,2003.Matchmaking of web services based on the daml-s service model.In:Proceedings of the Second Interna-tional Joint Conference on Autonomous Agents and Multi-agent Systems.

Ben Mokhtar,Sonia,Georgantas,Nikolaos,Issarny,Valerie,2005.Ad hoc composition of user tasks in pervasive computing environments.

In:Proceedings of the4th Workshop on Software Composition(SC 2005).Edinburgh,UK,April2005.LNCS.

Ben Mokhtar,Sonia,Liu,Jinshan,Georgantas,Nikolaos,Issarny, Valerie,2005.Qos-aware dynamic service composition in ambient intelligence environments.In:Proceedings of the20th IEEE/ACM International Conference on Automated Software Engineering (ASE’05).

Ben Mokhtar,Sonia,Georgantas,Nikolaos,Issarny,Valerie,2006.

Cocoa:Conversation-based service composition in pervasive comput-ing environments.In:Proceedings of the IEEE International Confer-ence on Pervasive Services(ICPS’06).

Ben Mokhtar,Sonia,Kaul,Anupam,Georgantas,N.,Issarny,Valerie, 2006.E?cient semantic service discovery in pervasive computing environments.In:Proceedings of ACM/IFIP/USENIX7th Interna-tional Middleware Conference(Middleware’06).

Ben Mokhtar,Sonia,Kaul,Anupam,Georgantas,Nikolaos,Issarny, Valerie,2006.Towards e?cient matching of semantic web service capabilities.In:Proceedings of the workshop of Web Services Modeling and Testing(WS-MATE’06).Berners-Lee,Tim,Hendler,James,Lassila,Ora,2001.The semantic web.

Scienti?c American.

Bernstein,A.,Klein,M.,2002.Towards high-precision service retrieval.

In:Proceedings of The First International Semantic Web Conference (ISWC’02).

Brogi,A.,Cor?ni,S.,Popescu,R.,https://www.wendangku.net/doc/b58207303.html,position-oriented service discovery.In:Proceedings of the4th Workshop on Software Compo-sition(SC’05).

Cardoso,Jorge,Sheth,Amit Miller,John,Arnold,Jonathan,Kochut, Krys,2004.Quality of Service for work?ows and Web service processes.Journal of Web Semantic.

Dijk,H.V.,Langendoen,K.,Sips,H.,2000.ARC:a bottom-up approach to negotiated QoS.In:IEEE Workshop on Mobile Computing Systems and Applications(WMCSA2000),December,2000.

Flinn,J.,Park,S.Y.,Satyanarayanan,M.,2002.Balancing performance, energy,and quality in pervasive computing.In:Proceedings of IEEE ICDCS.

Foster,Howard,Uchitel,Sebastian,Magee,Je?,Kramer,Je?,2003.

Model-based veri?cation of web service compositions.In:IEEE International Conference on Automated Software Engineering. Gurun,S.,Krintz, C.,Wolski,R.,2004.NWSLite:a light-weight prediction utility for mobile devices.In:Proceedings of ACM MobiSys.

Issarny,Valerie,Liu,Jinshan,2004.QoS-aware service location in mobile ad-hoc networks.In:IEEE International Conference on Mobile Data Management(MDM’04).

Issarny,Valerie,Sacchetti,Daniele,Tartanoglu,Ferda,Sailhan,Franc-oise,Chibout,Ra?k,Levy,Nicole,Talamona,Angel,2004.Develop-ing ambient intelligence systems:A solution based on web services.

Journal of Automated Software Engineering.

Koshkina,M.,van Breugel,F.,2003.Veri?cation of business processes for Web services.Technical report.York University.

Majithia,Shalil,Walker,David W.,Gray,W.A.,2004.A framework for automated service composition in service-oriented architecture.In: First European Semantic Web Symposium.

Masuoka,Ryusuke,Parsia,Bijan,Labrou,Yannis,2003.Task computing –the semantic web meets pervasive computing.In:Second Interna-tional Semantic Web Conference(ISWC2003).

Menasce,D.,https://www.wendangku.net/doc/b58207303.html,posing Web services:A QoS view.IEEE Internet Computing8(6).

Narayanan,D.,Satyanarayanan,M.,2003.Predictive resource manage-ment for wearable computing.In:Proceedings of ACM MobiSys. Patil,Abhijit A.,Oundhakar,Swapna A.,Sheth,Amit P.,Verma,Kunal, 2004.Meteor-s web service annotation framework.In:Proceedings of the13th Conference on World Wide Web.

Roman,Manuel,Hess,Christopher,Cerqueira,Renato,Ranganathan, Anand,Campbell,Roy H.,Nahrstedt,Klara,2002.Gaia:a middle-ware platform for active spaces.SIGMOBILE Mobile Computing and Communication Review6(4).

Sabata,B.,Chatterjee,S.,Davis,M.,Sydir,J.J.,Lawrence,T.F.,1997.

Taxonomy for QoS speci?cation.In:Proceedings of Workshop on Object-oriented Real-time Dependable Systems(WORDS97),New-port Beach,California,USA.

Sousa,Joao Pedro,Garlan,David,2002.Aura:an architectural frame-work for user mobility in ubiquitous computing environments.In: Proceedings of the IFIP17th World Computer Congress–TC2 Stream/3rd IEEE/IFIP Conference on Software Architecture.

The DAML Services Coalition,2004.Bringing semantics to web services: The owl-s approach.In:Proceedings of the First International Workshop on Semantic Web Services and Web Process Composition (SWSWPC’04).

van der Aalst,W.M.P.,ter Hofstede,A.H.M.,2004.Yawl:Yet another work?ow https://www.wendangku.net/doc/b58207303.html,rmation Systems.

S.Ben Mokhtar et al./The Journal of Systems and Software80(2007)1941–19551955

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社区卫生服务中心个人先进事迹材料 xx，女，1972年11月出生，1991年就读于xx中医学院，1994年毕业后分配到武义桃溪中心卫生院工作，主要从事内科、儿科工作，1998年加入中国共产党，XX年调入武义xx街道社区卫生服务中心工作，从事全科医疗、社区责任医生、儿童保健工作。 为了提高她的诊疗技术，她外出进修学习。1999年她主动到武义第一人民医院儿科进修，通过半年的学习，她提高了儿科诊疗技术，回到单位后，方便了当地的群众。以前，小孩子生病家长喜欢到县城诊治，自从她进修回去之后，由于她的技术好，服务态度好，加上当时她也是当地的儿童保健医生，找她看病的人越来越多，半夜经常有患儿家长来敲门，不是值班时间她也热情接待，毫无怨言。XX年有一对住在医院附近的龙凤胎，先后三天内均患了支气管肺炎，当时两婴儿病情均较重，一般情况下，均需要住院治疗，但家里因生他们破腹产花了上万元，已经欠下一笔债，实在无钱住院，在这种情况下，她尽量为他们节省费用，两婴儿肺炎先后输液半个月，花费大概600元左右，经过她的精心诊治，双胞胎均获得了痊愈，两婴儿露出了灿烂的笑容，她这个医生也露出了欣慰的笑容。从此，这家人无论小孩生病，还是大人生病，均喜欢找她看病，她成了这家的家庭医生。

她工作认真负责，她也爱好学习。XX年自学取得浙江中医学院中医本科学历，并获得医学学士学位。XX年再次外出进修，在金华中心医院儿科学习一年。由于工作的需要，她觉得自己从事西医临床为主，应该西医临床理论要加强，于是她参加了XX年的温州医学院临床医学本科函授，XX年顺利获得温州医学院临床医学本科学历，并获得XX届温州医学院优秀毕业生称号。XX年参加浙江全科医学岗位培训，转型为一名全科医生。 XX年5月她调入武义白洋街道社区卫生服务中心工作，同年6月中心安排她到白溪社区服务站工作，分管站里的日常门诊，同时兼做社区责任医生，负责三个村1800人口。当时接手时她感觉压力很大。通过中心的多次培训及自己认真学习国家基本公共卫生服务规范，她慢慢理清了头绪，工作由被动转主动。当时白洋街道社区卫生服务中心医务人员严重缺乏，她在白溪社区卫生服务站上班，4位医务人员， 2名医生，2名护士，上午主要保证日常诊疗工作，晚上还要隔一天值班。下乡只能是下午或者休息天，所以她只能加班加点。一方面她充分利用xx社区服务站的优势，努力提高医生的诊疗水平，切实解决患者的病痛，取得当地群众对社区卫生服务站的信任。另一方面，她积极主动下村，深入每户人家进行随访，发放健康宣教资料，对慢性病、重点人群进行干预。