ENHANCED QUALITY OF SERVICE (QoS) FOR SIMILARITY COMPUTING IN

WEB SERVICE DISCOVERY

ABSTRACT
This study aims to figure out the best possible web service is the one that completely fulfills the
required functions while satisfying the QoS requested by a user. In this paper, we introduce a
new enhanced context based solution based on QoS (Quality of Service) for computing similarity
exploiting both functional and non-functional user’s requirements and providing the user ability
to control and proceed the discovery of web services, i.e. the main aim of this work is to locate
the appropriate web service correspondence with the context of the user by computing the
similarity.
1. INTRODUCTION
A web service is defined a service offered by an electronic device to another electronic
device, communicating with each other via the World Wide Web. In a Web service, Web
technology such as HTTP, originally designed for human-to-machine communication, is utilized
for machine-to-machine communication, more specifically for transferring machine readable file
formats such as XML (eXtensible Markup Language) and JSON (JavaScript Object Notation).
The Working Principle of Web Services are (i)The Service Provider publishes a description
of the services it offers via the Service Registry. (ii)The Service Consumer could be a person or a
program searches the service registry (The registry provides a central place where developers
(Service Providers) can publish new services or find existing ones.) to find a service that meets
their needs.(iii)If the service is available in the registry, the Service Consumer uses the service
offered by the Service Provider with the help of Binding process. If it is not available the registry
intimates the non-availability of the requested service to the Consumer.
The contributions of Enhanced QoS for Similarity Computing in Web Service Discovery are
the followings: 1) Proposing and developing a web service discovery framework that exploits
both functional and non-functional features of web services. 2)The framework utilizes the
SeqDisc approach to filter services determining the relevant services that represent functional
requirement of the user. 3)Then, both contextual information of the user and relevant services are
matched by measuring the similarity between them. 4)These services are then ranked, which can
in this context, achieve both functional and non-functional requirements of the user.
5)Conducting a set of experiments to validate the effectiveness of the proposed framework
comparing it with three different methods.
Web Services are applied in the field of IoT (Internet of Things) , E-Commerce websites ,
Virtual Reality , Multimedia , Web Development Companies
LITERATURE REVIEW
 In the paper, Semantic web service search: a brief survey (University of Zurich,
Zurich Open Repository and Archive University of Zurich Main Library Strickh of
Strasse 39) , they provided a brief survey of approaches for centralized and decentralized
search of semantic web services. There are quite a few and sophisticated techniques for
 this purpose with various applications in different domains which make use of them in
order to achieve a more precise service selection.

 In the paper, Semantic Web service discovery: state-of-the-art and research

challenges
(Institute for Infocomm Research (I2R)Agency for Science, Technology and
Research (A*STAR)Singapore) they provide an extensive review of semantic Web
service discovery, highlighting the state-of-the-art approaches, the key semantic
formalisms employed, as well as benchmarks and testbeds for performance evaluation.
Defining a generic framework for semantic service discovery, we describe the key tasks
and criteria involved in agent-based computing. A detailed comparison of the popular
discovery systems is performed with a discussion on trade-offs between existing
approaches.

 The contributions of the paper, Web Services Discovery Based on Schema Matching
(School of Computer Science and Mathematics Victoria University Melbourne, VIC,
Australia)
are
1. A novel approach to retrieve desired web service operations of a given textual
description.
2. A new Schema Matching Algorithm is proposed for supporting webservice operations
matching. The key part of our algorithms is a schema tree matching algorithm, which
employs a new cost model to compute tree edit distances.
3. Based on operations matching, we use the agglomeration algorithm to cluster similar
webservice operations.
4. A ranking strategy is also introduced to satisfy a user’s top-k requirements.

 In the paper, Combining Schema and Level-Based Matching for Web Service
Discovery
(Department of Computer Science, University of Leipzig, Germany 2 Queensland
University of Technology, 2434 Brisbane, Australia 3 School of Computer Science,
University of Magdeburg, Germany),a new and flexible approach to assess the
similarity between WSs, which can be used to support a more automated WS discovery
framework. The approach makes use of the whole WSDL document specification and
distinguishes between the concrete and abstract parts. The concrete parts from different
Web services have the same hierarchal structure, hence we devised a level-based
matching approach. The abstract parts have different structures, therefore, we developed
a sequence-based schema matching approach to compute the similarity between them.

 The contribution of the paper Improving Web Service Discovery by using Semantic
Models
(Faculty of Information Technology, Queensland University of Technology,
Australia) is two-fold. Firstly, a novel Web service discovery method based on the
 semantic similarity derived from the trained support-based kernel is introduced. We
propose the creation of latent semantic kernel with the support-based algorithm using the
concept of binning & merging, and then utilize the kernel to find semantically similar
Web services for a user query. Secondly, a thorough practical experimentation and
evaluation have been performed. The empirical analysis confirms that the proposed
method is able to find semantic relations and thereby to improve the process of Web
service discovery in comparison to traditional methods.

 In the paper, A Framework for QoS-Aware Binding and Re-Binding of Composite

Web Services
(RCOST — Research Centre on Software Technology Department of Engineering –
University of Sannio Viale Traiano – 82100 Benevento, Italy),GAs-based approach for
QoS-aware service binding and a method to trigger and enact run-time re-binding; we
present an integrated framework, that permits the creation and execution of compositions
of abstract services, and the monitoring of QoS attributes. Whilst the framework has been
implemented to cope with WS-BPEL compositions, it can be easily adapted to other
composition languages.

 The paper Towards QoS-Based Web Services Discovery (School of Information

Systems and Technology University of Wollongong Wollongong, NSW, Australia
2522) proposes a generic model to represent QoS information in service advertisements
as well as QoS requirements in service discovery requests. Based on this model, a
matching algorithm and a ranking algorithm are presented. Given a service discovery
request, the matching algorithm compares its QoS requirements with the QoS
advertisements in the repository and locates those services with matching QoS. The
ranking algorithm furthers ranks these discovered services to facilitate the consumers to
select services.

 With reference to the paper, Semantic Web Service Composition Through a P2P-
Based Multi-Agent Environment (Norwegian University of Science and Technology
Department of Computer and Information Science Trondheim, Norway. 2 Royal
Institute of Technology Department of Microelectronics and Information
Technology Kista, Sweden), they describe an implementation of a Multi Agent
System(MAS) where agents cooperatively apply distributed symbolic reasoning for
discovering and composing Semantic Web Services.
A structured P2P network is used to self organise MAS infrastructure for efficient
resource discovery. In addition, if no services satisfying user requirements are found then
Cooperative Problem Solving (CPS) is applied for dynamic construction of new
composite web services.

 In the paper, Personalized QoS Prediction for Web Services via Collaborative
Filtering
 (Software Institute, EECS, Peking University, P.R. China 2 Key Laboratory of High
Confidence Software Technologies, Ministry of Education of P.R. China), many
researchers propose that, not only functional but also non-functional properties, also
known as quality of service (QoS), should be taken into consideration when consumers
select services. Consumers need to make prediction on quality of unused web services
before selecting. Usually, this prediction is based on other consumers’ experiences. Being
aware of different QoS experiences of consumers, this paper proposes a collaborative
filtering based approach to making similarity mining and prediction from consumers’
experiences.

 The main features of the proposed approach in the reference paper QoS-aware query
relaxation for service discovery with business rules (Department of Computer
Science and Engineering, National Taiwan Ocean University, Keelung 202, Taiwan)
are as follows: (1) a business rule annotation mechanism that includes condition rules,
enumeration rules, and applied utility references; (2) the ability to eliminate unsuitable
services through the application of filters to deal with kernel properties, provider
constraints, and user constraints; (3) the calculation of service ranking scores for single
services or service sets according to QoS constraints and QoS importance ranking; and
(4) the ability to retrieve suitable single services as well as service sets using the
proposed two-point and incremental service query relaxation mechanisms.

 The paper QoS-based Discovery and Ranking of Web Services (Department of

Computing and Information Science University of Guelph, Guelph, Ontario, N1G
2W1 Canada) introduces a mechanism that extends our Web Services Repository
Builder (WSRB) architecture [1] by offering a quality-driven discovery of Web services
and uses a combination of Web service attributes as constraints when searching for
relevant Web services. Our solution has been tested and results show high success rates
of having the correct or most relevant Web service of interest within top results. Results
also demonstrate the effectiveness of using QoS attributes as constraints when
performing search requests and as elements when outputting results. Incorporating QoS
properties when finding Web services of interest provides adequate information to
service requestors about service guarantees and gives them some confidence as to the
quality of Web services they are about to invoke.

 The paper A Model for Web Services Discovery with QoS (CSIRO Mathematical and
Information Sciences GPO Box 664, Canberra, ACT 2601, Australia) proposes a new
Web services discovery model in which the functional and non-functional requirements
(i.e. quality of services) are taken into account for the service discovery. The proposed
model should give Web services consumers some confidence about the quality of service
of the discovered Web services.

 The paper Web services clustering using SOM(Self Organizing Map) based on kernel
cosine similarity measure College of Computer Science & Technology, Nanjing
 University of Posts and Telecommunications, 210003, Jiangsu, China) first presents
a WordNet-VSM (W-VSM) model for Web services representation which not only
enriches the conventional VSM feature vectors' semantic information but also reduce
their dimension and sparsity. Then a set of kernel cosine similarity measures are proposed
to well estimate the similarity of the Web services. Furthermore, an unsupervised SOM
neural network algorithm based on aforementioned kernel cosine similarity measure
(KCSOM) is presented to automatically cluster Web services. Finally, the preliminary
experiments using real-world Web services demonstrate the feasibility of the proposed
approach.

 In the paper, A Framework for Context-Aware Adaptable Web Services

(University at Passau, D-94030 Passau, Germany) , we present a context framework
that facilitates the development and deployment of context-aware adaptable Web
services. We implemented the framework within our Service Globe system [1,2], an open
and distributed Web service platform. In our framework, context information is
transmitted (in XML data format) as a SOAP header block within the SOAP messages
that Web services receive and send. A context header block contains several context
blocks. Each context block is associated with one dedicated context type, which defines
the type of context information a context block is allowed to contain. At most one context
block for a specific context type is allowed.

 In the paper Similarity Search for Web Services (University of Washington, Seattle)
1. They propose a basic set of search functionalities that an effective web-service search
engine should support.
2. They describe algorithms for supporting similarity search. Our algorithms combine
multiple sources of evidence in order to determine similarity between a pair of web-
service operations. The key ingredient of our algorithm is a novel clustering algorithm
that groups names of parameters of web-service operations into semantically meaningful
concepts. These concepts are then leveraged to determine similarity of inputs (or outputs)
of web-service operations.
3. They describe a detailed experimental evaluation on a set of over 1500 web-service
operations. The evaluation shows that we can provide both high precision and recall for
similarity search, and that our techniques substantially improve on naive keyword search.

3. RELATED WORKS
A web service discovery is established with expressions like keyword, request, mapping or
matching. Various approaches have been offered to address and cope with web service discovery
challenges. In the early work, web service discovery was based on a syntactic or keyword
searches which measure accordance between the user query and descriptions of service, but the
appearance of new techniques such as semantic discovery, makes this technique have primarily
semantic which measure the similarity between the user query and the semantic description
service.
In the following, we discuss web service discovery approaches, which covers these different
aspects.
1) Syntactic-based approaches: The idea of these approaches is very simple, where the user
sends a request having keywords. These keywords are compared with descriptions of services
stored on service brokers. Despite to their facility and simplicity in implementation, these
approaches have some limitations because they do not present good results for the user and their
software cannot test the textual descriptions prepared for human using. The approach presents a
model for the similar syntactic matchmaking. This model represents a combination of interface,
attributes and QoS similarities with lexical similarity. This solution aims to join all nodes of the
arbitrary number either a federation or a cloud to exist in the UDDI virtual register. There is a
service description part in each node. When the user sends a message requesting one of these
nodes, the request moves from each node to its neighbor, and repeats this process for all nodes
which get this request. The results are provided in all nodes, and then are sent to the main node.
2) Semantic-based approaches: Approaches in this category are interested in the semantic
description of services. These approaches are fast growing due to their advantages that address
insufficiencies in syntactic-based approaches. In general, these approaches can be categorized
into either distributed or centralized architectures. Within the centralized architectures, there are
several ontologies that have been developed for this purpose. Examples are OWL S ontology and
DAML-S ontology (DARPA Agent Markup Language for Services), which depend on DAML-S
language. The iSeM approach , which is semantic matchmaker, that implements hybrid and
adaptive semantic matching of OWL S services. The logic based of services that belong to this
approach depends on the logical input/output concept subsumption relations, the accurate
computation and the logical plugin relation. The SPARQLent , which is semantic matching
approach that considers logic based and takes into account all functional profile of OWL S
services. The SeqDisc approach, which considers a semantic approach that assess the similarity
between WSs, taking into account both concrete and abstract part that form WSDL file in the
similarity process.
3) Context-based approaches: In general, the context can be defined as information that can
describe or characterize the case of an entity, where the entity can be considered as a place, a
person, or an object, which can be used to interact between application and user. In the context of
web services, either a user or a service may have their own contexts. The context of a service is
represented as QoS, localization, cost, etc. While, the context of a user is represented as his
preference, localization, etc. The approach makes use of ontology to enhance the concept of
context values of user and illustrates the relations between different context values in an
automatic way. Through these context value relations, the required services are suggested to the
user. The UDDI+ approach aims to apply the semantic discovery and discovers services
achieving user requirements. The CASD (Context Aware Service Discovery) approach is
introduced to provide a semantic web service discovery module. The approach makes use of
ontologies to exploit semantic similarity, which can be used to recommend the best services
corresponding to user requirement.
QoS-aware approaches: QoSs are responsible for the quality of the provided service and is used
to calculate the degree of similarity between user QoS request and QoS of provided services to
achieve high degree of quality according to user needs. A two-phase approach for web service
discovery depending on collaborative filtering approach and QoS is presented. The approach first
applies a collaborative filtering strategy as semantic matchmaking and then makes use of QoS
attributes as weights that can be given by user to get best recommended services according to
user needs with correct QoS information. In WSRB (Web Service Repository Builder)
approach , a web service crawler engine forwards many requests to various UDDI registries
according to user requests, and then collects all QoS results. The QoS of the services, which have
the same function will be represented in a matrix, and then all QoS attributes are normalized. The
similarity measure or ranking score will be calculated by a weighted sum of all values of QoS
attributes. The user puts the weight of each QoS attribute according to his preference. Then
developed a fuzzy-based solution for the discovery process that builds a model representing the
ranking of QoS-aware or non-functional web services as a fuzzy with different criteria for taking
problem decision. The BRSDE engine is for service discovery process. The objective of this
engine is: (i) considering QoS parameters to service description;(ii) providing business rule-
based service requests;(iii) executing business rule-based service discovery for the retrieval
services; and (iv) enhancing recommended services. The QoS values are used as rating in order
to provide similar users through realize similarity in QoS experience.
Some recent work has proposed annotating web services manually with additional semantic
information, and then using these annotations to compose services. In our context, annotating the
collection of web services is infeasible, and we rely on only the information provided in the
WSDL file and the UDDI entry.
4. ARCHITECTURE
5. CONCLUSION
An Enhanced QoS for Computing in Web Service Discovery has been presented in this paper for
the purpose of finding the best available Web service during Web services’ discovery process
based on a set of given clients QoS preferences. The use of non-functional properties for Web
services significantly improves the probability of having relevant output results. The proposed
solution has shown usefulness and effectiveness of incorporating QoS parameters as part of the
search criteria and in distinguishing Web services from one another during the discovery process.
The ability to discriminate on selecting appropriate Web services relied on the client’s ability to
identify appropriate QoS parameters. The proposed solution provides an effective Web service
degree of similarity function that is used for ranking and finding most relevant Web services.
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