a semantic approach for the enhancement of ranking of web services

8/14/2019 A Semantic Approach for the Enhancement of Ranking of Web Services

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AbstractWeb services are software components located

in the web which uses open protocols to communicate. A

web service is described by its WSDL document. Web

services allow clients to invoke procedures, functions, and

methods on remote objects. There are UDDI registries

pointing to the WSDL descriptions of the web services.

UDDI allows for the discovery of businesses, their web

services and the technical interfaces they make available.

A search engine takes input from the user, searches for

matching services in the repository and returns a set of

web service references to the user. The semantic

representation of a web service make the search much

context specific and meaningful. Ontology is used as a

mean for increasing the certainty of matching service

functionality. WSDL documents are converted to more

generic models and its operations are represented as a

tuple OP = , where I is a set of input messages,

and O is a set of output messages. C is a set of concepts,

belonging to a set of ontologies. M is a mapping between

input and output messages to concepts, which assigns a

probability value p [0, 1] that signifies the certainty of

the mapping. We propose to enhance the representation of

the semantic web service into a seven-tuple such that it is

an aid to improve the ranking of web services when the

result is given to the user by the search engine. We also

suggest some ideas for improving the response time of the

search engine.

Index Termsavailability, ontology, repository, semantic web

services

I.INTRODUCTION

he services that are available from the internet using

some standard protocols like HTTP or SMTP to access

are called web services. Remote procedures expose input and

output parameters that a web service must support. The clientqueries a UDDI registry for the service either by name,

category, identifier, or specification supported. Once located,

the client obtains information about the location of a WSDL

T

Manuscript received January 16, 2008.

N.S. Gowri Ganesh, Centrer for development of Advanced Computing, ,

A scientific society under Informaton & Commn. Tech.,Govt.of India, Chennai

(phone: 91-44-2461 0880; fax: 91-44-2461-0898; e-mail: [email protected]).

Viji Gopal is a Master of Engineering Student in R.M.K.Engineering

College, Kavaraipettai, Chennai (e-mail: [email protected]).

document from the UDDI registry. The UDDI registry

maintains pointers to the Web Service description and to the

service. The UDDI allows clients to search this registry, find

the intended service and retrieve its details.

Th emergence of Web Services developments and

standards in support of automated business integration has

driven major technological advances in the integration

software space, most notably, the Service Oriented

Architecture.

Paper Outline: The remainder of the paper is organized as

follows. Section 2 introduces the semantic web, Ontologies

and Four Tuple Representation. Section 3 and 4 proposes the

availability of web services with seven tuple representation.

We present the enhancing features in section 4, suggested

improvement in section 5 and conclude in section 6.

II.BACKGROUND

A.Semantic Web

Current web which can be assumed to be the biggest

global database lacks the existence of a semantic structure

to keep the interdependency of its components and as a

result the information available on web is mostly human

understandable. Semantic web provides some languages

that express information in a machine process-able format.

This implies that we can take more benefit from theirprocessing power. A huge amount of data are conceptually

related, but much of these relationships still have to be kept

in human memory and not stored in an understandable way

for machines. ultimate goal of Semantic Web is to create

some smarter content which could be understood by

machines. When the content is understood by machine,

some assertions may come out of the content and new

pieces of information will be produced.

Figure 1: The architecture of a search engine for web

services

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A Semantic Approach for the Enhancement of

Rankin of Web ServicesN.S Gowri Ganesh, Viji Gopal


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A search engine handles queries to retrieve web services.

(figure 1). It takes as input a set of input parameters of the

web services and a set of output parameters of the web

service. The search engine contains four parts: a Crawler,

an Index, a query interface, and a result interface. The

retrieved services are ranked and presented to the user via

the result interface. The crawler discovers, analyzes and

indexes semantic descriptions of Web services. The

structure of the index allows the questions above to beanswered, by indexing services according to the concepts

they relate to, and according to their relations with other

services.

B.Ontologies

During the last few years many Semantic Web related

technologies have emerged or have been elaborated. One of

the most important parts of these improvements is the status

of ontology development languages which looks to be more

stable now. The World Wide Web Consortium (W3C) who

has been working intensively on semantic standards, has

approved the Resource Definition Framework (RDF) andthe OWL Web Ontology Language (OWL) and hence

provides a solid base to establish enterprise semantic

applications and has implied a significant leverage of the

Semantic Web from a research level to an industry standard

for building next generation applications.

Ontologies are building blocks of Semantic Web based

systems. Creating ontologies is not an easy task and

obviously there is no unique correct ontology for any

domain. The real quality of ontology can be assessed only

by its use in real applications. its use in real applications.

Web services enable us to access relevant applications,

but the discovery, invocation and composition of web

services still need to be supported by human interaction.

This is the point where Semantic Web comes to play and to

support web services with ontologies as an added value.

Combining the strength of web services and the added value

of Semantic Web will result in a concrete base for enterprise

applications.

C.Four Tuple Representation

Eran toch et. al proposes a search engine which uses the

above said idea of combining semantic web with ontology.

This approach relies on ontologies as a mean for increasing

the certainty of matching service functionality. By using data

integration and conceptual model techniques, WSDL

documents are analyzed and transformed into a generic

service model. Following that, the service properties are

mapped to concepts that belong to ontologies in different

domains. For instance, a library service will be mapped to

ontologies that describe book-vendors, members and book-

title concepts. A Web service is described as a set of

operations WS = {OP1,OP2, ...,OPn}. The operations, rather

than the services themselves, are the elements which will be

matched against the query. An operation is defined as a tuple

OP = , where I is a set of input messages, and O is

a set of output messages. C is a set of concepts, belonging to a

set of ontologies. M is a mapping between input and output

messages to concepts, which assigns a probability value p

[0, 1] that signifies the certainty of the mapping.

The search query terms will be mapped to ontological

concepts in a similar way. We will define a query as a tuple

Query = , where E is a set of structured query

expressions (which are not formally defined in this paper). C

and M have the same meaning as in the formal model of Web

services described above. Figure depicts the conceptualmodels of operations and queries. The small-cap c denotes

concepts, while the i and o symbolizes the operations input

and output messages, respectively. The service-retrieval

problem is transformed from a mapping problem between a

query and a set of services to a mapping problem between a

set of query concepts and a set of service concepts.

The matching algorithm analyzes the ontology, using

related concepts and the structure of the ontology itself. The

results will be ranked according to the accumulated certainty

(over the set of query expressions, concepts and messages) of

the match between the query and the services.

III.SEVEN TUPLE REPRESENTATION

A.Concept of Fairness

As described above, a web service has been transformed

to concepts. Based on the affinity it is ranked and displayed

to the user. But the World Wide Web is so dynamic that it

changes every moment. The services available today may

not be working tomorrow and those who are down today

may be placed back on service tomorrow, after some

renovations or improvements. So the content of the

repository is also susceptible to this dynamic nature. The

index should show the changes that happen to the webservices listed in it.

We propose that the index should be able to show the

total time the web service was available to the user. The

availability of the web service,W during its entire life time

till the current time is termed as the fairness, Fof the web

service. This is an integer value. Time stamp, Trepresents

the time at which the last periodic check on web service,W

was performed. LatestStatus, L represents the status of W

at the time of the last availability check on it. L is a Boolean

value. We propose to add these three parameters along with

the standard parameters of the web service ontological

representation discussed in section II.C. Now the tuple

becomes .When the result reaches the user, he is shown the values

of F, T and L so that the user can know how reliable the

web service is and what is its present status at t hours

back.t is the difference between the current server system

time and the time stamp, T. The time when the last

availability verification was performed is not directly shown

to the user because of the geographical diversity of the

location of users. Different places have different time zones.

Showing the number of hours before what time an

availability verification was performed eases the

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complication of time conversion and ambiguities regarding

that.

Each of the parameters F, T and L is assigned an initial

value at the time the crawler enters it in the index. F is set

to an initial value of 0.500. Its maximum value is 0.999 and

minimum value is 0.001. Initial value of T is the system

time of the server at the time the web service is indexed for

the first time. Initial value of L is true.

B.Implementation of Fairness

The fairness of a web service should be calculated and

stored along with the description, in the index. We use a

verifierto update the fairness of a web service.

Figure 2: Enhanced Search Engine with Verifier

Figure 2 shows the structure of an enhanced search enginefor web services, with the verifier. The crawler crawls the

web and populates the index with the references to web

services. The verifier is invoked periodically to check the

current availability of the web services. It takes its input from

the index and checks each link in the index for liveness. It

tests the availability of a potential web service by invoking

one of its methods using randomly generated test data.

When the verifier performs an availability verification, if it

gets a SOAP response from the web service, it indicates that

the web service is in working condition. Now the verifier adds

0.001 to the current value of F. This indicates the

improvement of fairness. The higher the fairness value, the

more reliable the web service is. In other words, if the valueof F is above 0.900 it indicates that the web service was

available most of the time the verifier performed an

availability verification. If the web service was available

whenever the verifier was invoked, its value is 0.999 and does

not change further.

When the verifier performs an availability verification, if it

gets an HTTP error message, it indicates that the web service

is in not available at that time or it is permanently dead. Now

the verifier subtracts 0.001 from the current value of F. This

indicates the decrease of fairness. The lower the fairness

value, the less reliable the web service is. In other words, if

the value of F is below 0.2, it indicates that the web service

was not responding most of the time the verifier performed an

availability verification. If the web service was not responding

whenever the verifier was invoked, its value is 0.001 and does

not change further.

C.Effect on Ranking

A web service search engine based on ontology ranks the

results in the following way. It checks the affinity between the

concepts describing the query and the service. The services

which has high affinity is given high ranking. But this

method can not ensure that a service with a high ranking is

available all the time or most of the time. Sometimes the

service may have been listed, have worked for some time and

shut down after a while.

Our approach ensures that the user is able to know the

responsiveness of a web service when the search engine gives

a result set. From the value of F, user can know how fair the

web service have been during its life time. Also he can know

the latest status of the web service at thours back when theavailability verifier performed its last check. So even if a web

service was down for a long time and its fairness value is very

low, the user may opt for giving a shot for that web service if

L shows the service is available when it was last checked.

IV.ENHANCING FAIRNESS

There are two chances that a web service does not respond

when the verifier invokes it. It may be shut down or the server

may be busy. In the latter case, actually the web service is

working but not available at present. In this case, we can

subtract a value of 0.0005 from the current value of F. Thisavoids mistaking a web service as a dead one.

V.SUGGESTED IMPROVEMENTFORBETTERPERFORMANCEOFTHE

REPOSITORY

We plan to improve the response time of the search engine

by providing a cache effect to its output interface making use

of the concept of ontology.

VI.CONCLUSIONAND FUTURE WORKEven when a rich set of ontologies is built the ontology

engineering process is not terminated, the next problem we

should deal with is the issue of ontology aging. Results,

extracted from an out-of-dated ontology can not be used in a

totally meaningful way. There should be some mechanism to

detect ontology aging and force the semantic based systems to

evolve ontologies as environmental parameters are changing.

Multilingual support is recognized as one of the most

important challenges of Semantic Web. Nowadays English is

the predominating language and about 70 percent of Internet

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content is in English, but only about 44 percent of Internet

users are native English speakers. Especially in India this

issue is quite essential and the diversity of languages needs to

be taken into consideration. One method to handle this

problem is by establishing relevant inter-ontology translators

that map ontologies and content to other languages.

Also we are planning to extend the current research such

that the search engine can identify trusted service providers

because trust is something that is given very high importancein todays business world.

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