With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their
functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
USER-CENTRIC OPTIMIZATION FOR CONSTRAINT WEB SERVICE COMPOSITION USING A FUZZ...ijwscjournal
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed environments. In such systems, however each service responds the user request independently, it is essential to compose them for delivering a compound value-added service. Since, there may be a number of compositions to create the requested service, it is important to find one which its properties are close to user’s desires and meet some non-functional constraints and optimize criteria such as overall cost or response time. In this paper, a user-centric approach is presented for evaluating the service compositions
which attempts to obtain the user desires. This approach uses fuzzy logic in order to inference based on quality criteria ranked by user and Genetic Algorithms to optimize the QoS-aware composition problem. Results show that the Fuzzy-based Genetic algorithm system enables user to participate in the process of web service composition easier and more efficient.
Immune-Inspired Method for Selecting the Optimal Solution in Semantic Web Ser...IJwest
The increasing interest in developing efficient and effective optimization techniques has conducted researchers to turn their attention towards biology. It has been noticed that biology offers many clues for designing novel optimization techniques, these approaches exhibit self-organizing capabilities and permit the reachability of promising solutions without the existence of a central coordinator. In this paper we handle the problem of dynamic web service composition, by using the clonal selection algorithm. In order to assess the optimality rate of a given composition, we use the QOS attributes of the services involved in the workflow as well as, the semantic similarity between these components. The experimental evaluation shows that the proposed approach has a better performance in comparison with other approaches such as the genetic algorithm.
AN ARCHITECTURE FOR WEB SERVICE SIMILARITY EVALUATION BASED ON THEIR FUNCTION...ijwscjournal
By increasing popularity of SOC, using Web services in applications has increased too. SOC creates a loosely coupled environment in which the actual execution environment might differ significantly from the one with the presupposed conditions during application design. Therefore, although an appropriate Web service might have been selected, by passing time, the Web service may not be efficient enough or may not be applicable under specific conditions.
For service-oriented systems to be flexible and self-adaptive, it is necessary to automatically select and use a similar service instead of the one which causes the above mentioned problems. Finding a similar service means specifying the proper services which fulfill the same requirements as those fulfilled by the problematic service.
In most of the previous works, a number of the best services (k) are selected and ordered based on functional similarity. The user must select one of these services based on his/her preferences. One important metric in selecting a similar service is considering QoS properties and user preferences about QoS. Because of the importance of this issue, in the present paper, an architecture is proposed in which, in addition to functional similarity, QoS properties and user preferences are also considered in selecting a similar service.
CLUSTERING-BASED SERVICE SELECTION FOR DYNAMIC SERVICE COMPOSITIONIJwest
The increase in the number of available web services led to the increase in the similarity of services functionality offered by different providers each with different QoS parameters. Therefore, in web service composition, the selection of the optimal service to satisfy the QoS values required by user is one of the significant requirements. Moreover, the dynamic nature of web services adds more challenges to obtain the accuracy of the selection process. Most of the existing service composition approaches deal with services changes during composition execution, causing a re-planning or re-selection that affecst the service composition performance. In this paper, we introduce the clustering-based service selection model that outperforms the existing ones. The proposed model has the ability to detect and recover the changes in service repository by monitoring the composition process from a global point of view. The approach is a two-levels-based web service clustering. The proposed model encompasses a clustering process, a planning process, a selection process and a recovery process.
AN ADAPTIVE APPROACH FOR DYNAMIC RECOVERY DECISIONS IN WEB SERVICE COMPOSITIO...ijwscjournal
Service Oriented Architecture facilitates automatic execution and composition of web services in
distributed environment. This service composition in the heterogeneous environment may suffer from
various kinds of service failures. These failures interrupt the execution of composite web services and
lead towards complete system failure. The dynamic recovery decisions of the failed services are
dependent on non-functional attributes of the services. In the recent years, various methodologies
have been presented to provide recovery decisions based on time related QoS (Quality of Service)
factors. These QoS attributes can be categorized further. Our paper categorized these attributes as
space and time. In this paper, we have proposed an affinity model to quantify the location affinity for
composition of web services. Furthermore, we have also suggested a replication mechanism and
algorithm for taking recovery decisions based on time and space based QoS parameters and usage
pattern of the services by the user.
WEB SERVICE COMPOSITION IN DYNAMIC ENVIRONMENT: A COMPARATIVE STUDYcscpconf
This document provides a comparative study of 16 recent research papers on web service composition in dynamic environments. It evaluates the papers based on their approach to adapting to environmental changes, the composition phase they consider for detecting changes, whether they account for quality of service attributes, their main contributions, and whether they include experiments. The study finds that most approaches handle dynamism during the execution phase, treating earlier phases as static, and that more work is needed to detect and handle changes across all composition phases to build more reliable plans. Accounting for quality of service attributes and including experiments are also areas for improvement.
A HEURISTIC APPROACH FOR WEB-SERVICE DISCOVERY AND SELECTIONijcsit
This document proposes a new heuristic approach for web service discovery and selection using an algorithm inspired by honey bee behavior called the Bees Algorithm. The approach structures service registries by domain to simplify discovery. It uses the Bees Algorithm as an intelligent search method to efficiently find the optimal service matching a client's request and quality of service requirements from the relevant registry in least time.
Web Service Recommendation using Collaborative FilteringIRJET Journal
This document summarizes a research paper on using collaborative filtering techniques for web service recommendation. It discusses two collaborative filtering methods - Pearson Correlation Coefficient (PCC) and Normalized Recovery Collaborative Filtering (NRCF). PCC and NRCF calculate similarity between users or services based on quality of service (QoS) metrics to find similar users/services and recommend services. The document explains the techniques used in PCC and NRCF for similarity computation and QoS value prediction.
USER-CENTRIC OPTIMIZATION FOR CONSTRAINT WEB SERVICE COMPOSITION USING A FUZZ...ijwscjournal
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed environments. In such systems, however each service responds the user request independently, it is essential to compose them for delivering a compound value-added service. Since, there may be a number of compositions to create the requested service, it is important to find one which its properties are close to user’s desires and meet some non-functional constraints and optimize criteria such as overall cost or response time. In this paper, a user-centric approach is presented for evaluating the service compositions
which attempts to obtain the user desires. This approach uses fuzzy logic in order to inference based on quality criteria ranked by user and Genetic Algorithms to optimize the QoS-aware composition problem. Results show that the Fuzzy-based Genetic algorithm system enables user to participate in the process of web service composition easier and more efficient.
Immune-Inspired Method for Selecting the Optimal Solution in Semantic Web Ser...IJwest
The increasing interest in developing efficient and effective optimization techniques has conducted researchers to turn their attention towards biology. It has been noticed that biology offers many clues for designing novel optimization techniques, these approaches exhibit self-organizing capabilities and permit the reachability of promising solutions without the existence of a central coordinator. In this paper we handle the problem of dynamic web service composition, by using the clonal selection algorithm. In order to assess the optimality rate of a given composition, we use the QOS attributes of the services involved in the workflow as well as, the semantic similarity between these components. The experimental evaluation shows that the proposed approach has a better performance in comparison with other approaches such as the genetic algorithm.
AN ARCHITECTURE FOR WEB SERVICE SIMILARITY EVALUATION BASED ON THEIR FUNCTION...ijwscjournal
By increasing popularity of SOC, using Web services in applications has increased too. SOC creates a loosely coupled environment in which the actual execution environment might differ significantly from the one with the presupposed conditions during application design. Therefore, although an appropriate Web service might have been selected, by passing time, the Web service may not be efficient enough or may not be applicable under specific conditions.
For service-oriented systems to be flexible and self-adaptive, it is necessary to automatically select and use a similar service instead of the one which causes the above mentioned problems. Finding a similar service means specifying the proper services which fulfill the same requirements as those fulfilled by the problematic service.
In most of the previous works, a number of the best services (k) are selected and ordered based on functional similarity. The user must select one of these services based on his/her preferences. One important metric in selecting a similar service is considering QoS properties and user preferences about QoS. Because of the importance of this issue, in the present paper, an architecture is proposed in which, in addition to functional similarity, QoS properties and user preferences are also considered in selecting a similar service.
CLUSTERING-BASED SERVICE SELECTION FOR DYNAMIC SERVICE COMPOSITIONIJwest
The increase in the number of available web services led to the increase in the similarity of services functionality offered by different providers each with different QoS parameters. Therefore, in web service composition, the selection of the optimal service to satisfy the QoS values required by user is one of the significant requirements. Moreover, the dynamic nature of web services adds more challenges to obtain the accuracy of the selection process. Most of the existing service composition approaches deal with services changes during composition execution, causing a re-planning or re-selection that affecst the service composition performance. In this paper, we introduce the clustering-based service selection model that outperforms the existing ones. The proposed model has the ability to detect and recover the changes in service repository by monitoring the composition process from a global point of view. The approach is a two-levels-based web service clustering. The proposed model encompasses a clustering process, a planning process, a selection process and a recovery process.
AN ADAPTIVE APPROACH FOR DYNAMIC RECOVERY DECISIONS IN WEB SERVICE COMPOSITIO...ijwscjournal
Service Oriented Architecture facilitates automatic execution and composition of web services in
distributed environment. This service composition in the heterogeneous environment may suffer from
various kinds of service failures. These failures interrupt the execution of composite web services and
lead towards complete system failure. The dynamic recovery decisions of the failed services are
dependent on non-functional attributes of the services. In the recent years, various methodologies
have been presented to provide recovery decisions based on time related QoS (Quality of Service)
factors. These QoS attributes can be categorized further. Our paper categorized these attributes as
space and time. In this paper, we have proposed an affinity model to quantify the location affinity for
composition of web services. Furthermore, we have also suggested a replication mechanism and
algorithm for taking recovery decisions based on time and space based QoS parameters and usage
pattern of the services by the user.
WEB SERVICE COMPOSITION IN DYNAMIC ENVIRONMENT: A COMPARATIVE STUDYcscpconf
This document provides a comparative study of 16 recent research papers on web service composition in dynamic environments. It evaluates the papers based on their approach to adapting to environmental changes, the composition phase they consider for detecting changes, whether they account for quality of service attributes, their main contributions, and whether they include experiments. The study finds that most approaches handle dynamism during the execution phase, treating earlier phases as static, and that more work is needed to detect and handle changes across all composition phases to build more reliable plans. Accounting for quality of service attributes and including experiments are also areas for improvement.
A HEURISTIC APPROACH FOR WEB-SERVICE DISCOVERY AND SELECTIONijcsit
This document proposes a new heuristic approach for web service discovery and selection using an algorithm inspired by honey bee behavior called the Bees Algorithm. The approach structures service registries by domain to simplify discovery. It uses the Bees Algorithm as an intelligent search method to efficiently find the optimal service matching a client's request and quality of service requirements from the relevant registry in least time.
Web Service Recommendation using Collaborative FilteringIRJET Journal
This document summarizes a research paper on using collaborative filtering techniques for web service recommendation. It discusses two collaborative filtering methods - Pearson Correlation Coefficient (PCC) and Normalized Recovery Collaborative Filtering (NRCF). PCC and NRCF calculate similarity between users or services based on quality of service (QoS) metrics to find similar users/services and recommend services. The document explains the techniques used in PCC and NRCF for similarity computation and QoS value prediction.
Reliability evaluation model for composite web servicesdannyijwest
Web services are the new innovation in this era. Because of the cross-platform and language independent nature of the web
services, it is getting accepted by the various industries. Revolution in Service Oriented Architecture (SOA) has created
numerous web service users. Different choices of services are available to meet the specific requirement of customers. At the
same time, customer needs quality service. Selecting the web service which meets all the Quality of Service (QoS) requirement
specified by the consumer in the Service Level Agreement is a tedious task today. One of the predominant QoS factor is
reliability of the web service. Evaluation of reliability on web services and selecting the best one among the different choices are
needed now. This paper focuses on the design of reliability evaluation framework for the composite web services.
Location-Aware and Personalized Collaborative Filtering for Web Service Recom...1crore projects
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
An analytic network process and trapezoidal interval-valued fuzzy technique f...University of Piraeus
Next generation wireless networks consist of many heterogeneous access technologies that should support various service types with different quality of service (QoS) constraints, as well as user, requirements and provider policies. Therefore, the need for network selection mechanisms that consider multiple factors must be addressed. In this paper, a network selection method is proposed by applying the analytic network process to estimate the weights of the selection criteria, as well as a fuzzy version of technique for order preference by similarity to ideal solution to perform the ranking of network alternatives. The method is applied to a heterogeneous network environment providing different QoS classes and policy characteristics. Each user applies the method to select the most appropriate network, which satisfies his or her requirements in respect of his or her service-level agreement (SLA). Performance evaluation shows that when the user requests only one service, the proposed method performs better compared to the original technique for order preference by similarity to ideal solution, as well as the Fuzzy AHP-ELECTRE method. Moreover, the proposed method can be applied in cases where a user requires multiple services simultaneously on a device. The sensitivity analysis of the proposed method shows that it can be properly adjusted to conform to network environment changes.
SERVICE ORIENTED QUALITY REQUIREMENT FRAMEWORK FOR CLOUD COMPUTINGijcsit
This research paper introduces a framework to identify the quality requirements of cloud computing services. It considered two dominant sub-layers; functional layer and runtime layer against cloud characteristics. SERVQUAL model attributes and the opinions of the industry experts were used to derive the quality constructs in cloud computing environment. The framework gives proper identification of cloud computing service quality expectations of users. The validity of the framework was evaluated by using
questionnaire based survey. Partial least squares-structural equation modelling (PLS-SEM) technique was
used to evaluate the outcome. The research findings shows that the significance of functional layer is
higher than runtime layer and prioritized quality factors of two layers are Service time, Information and
data security, Recoverability, Service Transparency, and Accessibility.
Collaborative Filtering Approach For QoS PredictionEditor IJMTER
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. Experimental results demonstrate that
this approach can make significant improvement on the effectiveness of QoS prediction for web
services.
Service-oriented computing is meant to support loose relationships between organizations; Serviceoriented
architectures often have the goal to integrate various distributed services of one or more
organizations in a flexible way to be able to quickly react on business changes.
Distributed services provided a new way of distributed computing that achieve the interoperability between
heterogonous application through platform and language independent interfaces. The creation of value
added services by composition of existing ones is gaining a significant momentum. Distributed service
composition is meant to support loose relationships between implemented services in order to provide new
functions. A composite service is the one resulting from the integration, coordination and synchronization
of different service components. In this paper, we generated A Services Composition Model (SCM) that
provides a general solution for the services composition problem by realizing the requirements of a new
service using the requirements of the already existing service. We explained in details all the steps of the
composition process; services registration, services discovery, services selection, services invoking, and
services integration. Although the SCM is not bounded to one particular algorithm to compose services, we
generated an application as an example to test our Service Composition Model.
We also generated the Services Composition Language (SCL) as a simple text-based language which
allows the user to express the requirements of his request, the inserted request will then be analyzed using
our Parsing Algorithm to determine the name of the requested services, after that our Service Composition
Algorithm will execute all the steps of the composition process and return the result of the composition to
the user.
Testing of web services Based on Ontology Management ServiceIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
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A review on framework and quality of service based web services discoveryMustafa Algaet
In consequence these services are nowadays accessible to the final clients. In the last few years, more
and more Web Services providing the same functionalities are available in the environment. In order to
select the best service adapted to client’s requests, we need some method capable to evaluate and
compare different services providing the same functionalities. In this context, Quality of service can be defined as the capability to respond to the requirements (constraints) of a client and to fulfill these
needs with the best criteria (preferences) established by the client. It is calculated based on the non-
functional properties of the service. This paper provides an overview of a research progress in Quality
of Service Based Web Services Discovery; it also highlights the issues that need to be investigated in
Quality of Service Based Web Services
SERVICE SELECTION BASED ON DOMINANT ROLE OF THE CHOREOGRAPHYijwscjournal
Web services are playing dominant role on Internet for e-business. The compositions of these services are used to meet business objectives. The web service choreography describes the external observable behavior
of these compositions. Many compositions may available for same functionality. These compositions cannot be distinguished on the basis of functional properties. This Quality of services (QoS) may help the user to select web services and to analyze composition of the web services. Web service choreography is going to dictate implementation of workflow. This workflow consists of several tasks. Each task is implemented by web services. These services are hosted in large numbers by different service providers on different service clusters. The mapping of service and task is difficult issue in run time environment. The interoperability between services is also a great problem. The selection of services is very big issue. In this paper we have proposed a bio-inspired selection algorithm based on dominant role and proposed a discovery infrastructure. We have also used the client behavior to improve the failure of the composition of the service.
FUZZY-BASED ARCHITECTURE TO IMPLEMENT SERVICE SELECTION ADAPTATION STRATEGYijwscjournal
One of the main requirements in service based applications is runtime adaptation to changes that occur in
business, user, environment, and computational contexts. Changes in contexts lead to QOS degrade.
Continues adaptation mechanism and strategies are required to stay service based applications(SBA) in
safe state. In this paper a framework for runtime adaptation in service based application isintroduced. It
checks user requirements change continuously and dynamically adopts architecture model. Also it checks
providers QOS attributes continuously and if adaptation requirement is triggered, runs service selection
adaptation strategy to satisfy user preferences. Thusit is a context aware and automatically adaptable
framework for SBA applications. Wehave implemented a fuzzy based system for web service selection unit.
Due to ambiguity of context’s data and cross-cutting effects of quality of services, using fuzzy would result
an optimised decision. Finally we illustrated that using of it has a good performance for web service based
applications.
A COMPARATIVE STUDY OF PROCESS MEDIATOR COMPONENTS THAT SUPPORT BEHAVIORAL IN...ijwscjournal
The document discusses behavioral incompatibility between web services and process mediation approaches to resolve it. It defines four levels of mismatches - data, functional, protocol, and deadlock - that can cause incompatibility. Process mediation involves generating a mediator service to resolve protocol-level mismatches and enable successful interaction. The paper reviews several state-of-the-art mediation components and approaches, and provides a comparative evaluation based on important criteria like expressiveness, automation, correctness and completeness.
User-Centric Optimization for Constraint Web Service Composition using a Fuzz...ijwscjournal
ABSTRACT
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed
environments. In such systems, however each service responds the user request independently, it is
essential to compose them for delivering a compound value-added service. Since, there may be a number of
compositions to create the requested service, it is important to find one which its properties are close to
user’s desires and meet some non-functional constraints and optimize criteria such as overall cost or
response time. In this paper, a user-centric approach is presented for evaluating the service compositions
which attempts to obtain the user desires. This approach uses fuzzy logic in order to inference based on
quality criteria ranked by user and Genetic Algorithms to optimize the QoS-aware composition problem.
Results show that the Fuzzy-based Genetic algorithm system enables user to participate in the process of
web service composition easier and more efficient.
USER-CENTRIC OPTIMIZATION FOR CONSTRAINT WEB SERVICE COMPOSITION USING A FUZZ...ijwscjournal
This document summarizes a research paper that proposes a user-centric approach for evaluating and optimizing constraint-based web service compositions using fuzzy logic and genetic algorithms. The approach uses fuzzy logic to model user preferences through quality criteria rankings. It then uses a genetic algorithm to optimize the composition process to maximize user satisfaction based on those fuzzy preferences. The results showed that the fuzzy-genetic algorithm system enables users to more easily and efficiently participate in and guide the web service composition process according to their needs and preferences.
MMUNE-INSPIRED METHOD FOR SELECTING THE OPTIMAL SOLUTION IN SEMANTIC WEB SE...dannyijwest
The increasing interest in developing efficient and effective optimization techniques has conducted
researchers to turn their attention towards biology. It has been noticed that biology offers many clues for
designing novel optimization techniques, these approaches exhibit self-organizing capabilities and permit
the reachability of promising solutions without the existence of a central coordinator. In this paper we
handle the problem of dynamic web service composition, by using the clonal selection algorithm. In order
to assess the optimality rate of a given composition, we use the QOS attributes of the services involved in
the workflow as well as, the semantic similarity between these components. The experimental evaluation
shows that the proposed approach has a better performance in comparison with other approaches such as
the genetic algorithm
AN ARCHITECTURE FOR WEB SERVICE SIMILARITY EVALUATION BASED ON THEIR FUNCTION...ijwscjournal
By increasing popularity of SOC, using Web services in applications has increased too. SOC creates a loosely coupled environment in which the actual execution environment might differ significantly from the one with the presupposed conditions during application design. Therefore, although an appropriate Web service might have been selected, by passing time, the Web service may not be efficient enough or may not be applicable under specific conditions.
For service-oriented systems to be flexible and self-adaptive, it is necessary to automatically select and use a similar service instead of the one which causes the above mentioned problems. Finding a similar service means specifying the proper services which fulfill the same requirements as those fulfilled by the problematic service.
In most of the previous works, a number of the best services (k) are selected and ordered based on functional similarity. The user must select one of these services based on his/her preferences. One important metric in selecting a similar service is considering QoS properties and user preferences about QoS. Because of the importance of this issue, in the present paper, an architecture is proposed in which, in addition to functional similarity, QoS properties and user preferences are also considered in selecting a similar service.
AN ARCHITECTURE FOR WEB SERVICE SIMILARITY EVALUATION BASED ON THEIR FUNCTION...ijwscjournal
By increasing popularity of SOC, using Web services in applications has increased too. SOC creates a loosely coupled environment in which the actual execution environment might differ significantly from the one with the presupposed conditions during application design. Therefore, although an appropriate Web service might have been selected, by passing time, the Web service may not be efficient enough or may not be applicable under specific conditions.
For service-oriented systems to be flexible and self-adaptive, it is necessary to automatically select and use a similar service instead of the one which causes the above mentioned problems. Finding a similar service means specifying the proper services which fulfill the same requirements as those fulfilled by the problematic service.
In most of the previous works, a number of the best services (k) are selected and ordered based on functional similarity. The user must select one of these services based on his/her preferences. One important metric in selecting a similar service is considering QoS properties and user preferences about QoS. Because of the importance of this issue, in the present paper, an architecture is proposed in which, in addition to functional similarity, QoS properties and user preferences are also considered in selecting a similar service.
AN ADAPTIVE APPROACH FOR DYNAMIC RECOVERY DECISIONS IN WEB SERVICE COMPOSITIO...ijwscjournal
Service Oriented Architecture facilitates automatic execution and composition of web services in distributed environment. This service composition in the heterogeneous environment may suffer from various kinds of service failures. These failures interrupt the execution of composite web services and lead towards complete system failure. The dynamic recovery decisions of the failed services are dependent on non-functional attributes of the services. In the recent years, various methodologies have been presented to provide recovery decisions based on time related QoS (Quality of Service) factors. These QoS attributes can be categorized further. Our paper categorized these attributes as space and time. In this paper, we have proposed an affinity model to quantify the location affinity for composition of web services. Furthermore, we have also suggested a replication mechanism and algorithm for taking recovery decisions based on time and space based QoS parameters and usage pattern of the services by the user.
QOS Aware Formalized Model for Semantic Web Service SelectionIJwest
Selecting the most relevant Web Service according to a client requirement is an onerous task, as innumerous number of functionally same Web Services(WS) are listed in UDDI registry. WS are functionally same but their Quality and performance varies as per service providers. A web Service Selection Process involves two major points: Recommending the pertinent Web Service and avoiding unjustifiable web service. The deficiency in keyword based searching is that it doesn’t handle the client request accurately as keyword may have ambiguous meaning on different scenarios. UDDI and search engines all are based on keyword search, which are lagging behind on pertinent Web service selection. So the search mechanism must be incorporated with the Semantic behavior of Web Services. In order to strengthen this approach, the proposed model is incorporated with Quality of Services (QoS) based Ranking of semantic web services.
This paper focuses on various concepts of Quality of Service associated with web services. Various QoS parameters like performance, availability, reliability and stability etc. are formalized in order to enhance the pertinence of web service selection. A QoS mediator agent based Web Service Selection Model is proposed where QoS Consultant acts as a Mediator Agent between clients and service providers. Model suggests user’s preferences on QoS parameter selection. The proposed model helps to select pertinent Web Service as per user’s requirement and reduce the human effort.. Further process of adding ontology with semantic web services is also illustrated here.
QOS OF WEB SERVICE: SURVEY ON PERFORMANCE AND SCALABILITYcscpconf
In today’s scenario, most of the organizations provide the services through the web. This makes the web service an important research area. In addition, early design and building web services, it is necessary to concentrate on the quality of web services. Performance is an important quality attributes that to be considered during the designing of web services. The expected
performance can be achieved by proper scheduling of resources and scalability of the system. Scalability is a desirable attribute of a process computer system or network. Poor scalability
can result in lacking system performance. Hence, in this paper, we have reviewed the literature available for the quality attributes of performance and scalability and identified the issues that
affect the quality attributes related to Web Services
An effective method for clustering-based web service recommendationIJECEIAES
Normally web services are classified by the quality of services; however, the term quality is not absolute and defined relatively. The quality of web services is measured or derived using various parameters like reliability, scalability, flexibility, and availability. The limitation of the methods employing these parameters is that sometimes they are producing similar web services in recommendation lists. To address this research problem, the novel improved clustering-based web service recommendation method is proposed in this paper. This approach is mainly dealing with producing diversity in the results of web service recommendations. In this method, functional interest, quality of service (QoS) preference, and diversity features are combined to produce a unique recommendation list of web services to end-users. To produce the unique recommendation results, we propose a varied web service classification order that is clustering-based on web services’ functional relevance such as non-useful pertinence, recorded client intrigue importance, and potential client intrigue significance. Additionally, to further improve the performance of this approach, we designed web service graph construction, an algorithm of various widths clustering. This approach serves to enhance the exceptional quality, that is, the accuracy of web service recommendation outcomes. The performance of this method was implemented and evaluated against existing systems for precision, and f-score performance metrics, using the research datasets.
CHARACTERIZATION OF USER-PERCEIVED QUALITY OF SERVICE (QOS) IN MOBILE DEVICES...ijwmn
This paper presents a user-centric and application-specific QoS assessment methodology for cellular
communication networks. Specifically, it uses the Analytic Hierarchy Process (AHP) to evaluate QoS as a
multi-criteria decision problem that represents how well cellular networks’ data services are perceived
given particular sets of application classes and relative to other networks servicing in the same area. As
part of the methodology, drive testing is performed to collect objective measurements associated with
identified QoS criteria for data services. Once drive testing is performed and data collected, multiple
networks are compared to determine the network that provides higher QoS based on users’ perception of
quality. The selection of the best performing network is based on the output provided by the AHP
approach, which is used as unified measurement of the perceived QoS by users on different networks. In
order to determine application-specific priorities, the approach presented uses three different application
classes, including Emergency, Business, and Personal. For each class, the relative importance of each
quality evaluation criteria is adjusted in the AHP procedure to reflect the priorities of the services
expected. Through several case studies, the approach is proven successful in providing a way for
analyzing user-centric QoS for application-specific scenarios.
Reliability evaluation model for composite web servicesdannyijwest
Web services are the new innovation in this era. Because of the cross-platform and language independent nature of the web
services, it is getting accepted by the various industries. Revolution in Service Oriented Architecture (SOA) has created
numerous web service users. Different choices of services are available to meet the specific requirement of customers. At the
same time, customer needs quality service. Selecting the web service which meets all the Quality of Service (QoS) requirement
specified by the consumer in the Service Level Agreement is a tedious task today. One of the predominant QoS factor is
reliability of the web service. Evaluation of reliability on web services and selecting the best one among the different choices are
needed now. This paper focuses on the design of reliability evaluation framework for the composite web services.
Location-Aware and Personalized Collaborative Filtering for Web Service Recom...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
An analytic network process and trapezoidal interval-valued fuzzy technique f...University of Piraeus
Next generation wireless networks consist of many heterogeneous access technologies that should support various service types with different quality of service (QoS) constraints, as well as user, requirements and provider policies. Therefore, the need for network selection mechanisms that consider multiple factors must be addressed. In this paper, a network selection method is proposed by applying the analytic network process to estimate the weights of the selection criteria, as well as a fuzzy version of technique for order preference by similarity to ideal solution to perform the ranking of network alternatives. The method is applied to a heterogeneous network environment providing different QoS classes and policy characteristics. Each user applies the method to select the most appropriate network, which satisfies his or her requirements in respect of his or her service-level agreement (SLA). Performance evaluation shows that when the user requests only one service, the proposed method performs better compared to the original technique for order preference by similarity to ideal solution, as well as the Fuzzy AHP-ELECTRE method. Moreover, the proposed method can be applied in cases where a user requires multiple services simultaneously on a device. The sensitivity analysis of the proposed method shows that it can be properly adjusted to conform to network environment changes.
SERVICE ORIENTED QUALITY REQUIREMENT FRAMEWORK FOR CLOUD COMPUTINGijcsit
This research paper introduces a framework to identify the quality requirements of cloud computing services. It considered two dominant sub-layers; functional layer and runtime layer against cloud characteristics. SERVQUAL model attributes and the opinions of the industry experts were used to derive the quality constructs in cloud computing environment. The framework gives proper identification of cloud computing service quality expectations of users. The validity of the framework was evaluated by using
questionnaire based survey. Partial least squares-structural equation modelling (PLS-SEM) technique was
used to evaluate the outcome. The research findings shows that the significance of functional layer is
higher than runtime layer and prioritized quality factors of two layers are Service time, Information and
data security, Recoverability, Service Transparency, and Accessibility.
Collaborative Filtering Approach For QoS PredictionEditor IJMTER
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. Experimental results demonstrate that
this approach can make significant improvement on the effectiveness of QoS prediction for web
services.
Service-oriented computing is meant to support loose relationships between organizations; Serviceoriented
architectures often have the goal to integrate various distributed services of one or more
organizations in a flexible way to be able to quickly react on business changes.
Distributed services provided a new way of distributed computing that achieve the interoperability between
heterogonous application through platform and language independent interfaces. The creation of value
added services by composition of existing ones is gaining a significant momentum. Distributed service
composition is meant to support loose relationships between implemented services in order to provide new
functions. A composite service is the one resulting from the integration, coordination and synchronization
of different service components. In this paper, we generated A Services Composition Model (SCM) that
provides a general solution for the services composition problem by realizing the requirements of a new
service using the requirements of the already existing service. We explained in details all the steps of the
composition process; services registration, services discovery, services selection, services invoking, and
services integration. Although the SCM is not bounded to one particular algorithm to compose services, we
generated an application as an example to test our Service Composition Model.
We also generated the Services Composition Language (SCL) as a simple text-based language which
allows the user to express the requirements of his request, the inserted request will then be analyzed using
our Parsing Algorithm to determine the name of the requested services, after that our Service Composition
Algorithm will execute all the steps of the composition process and return the result of the composition to
the user.
Testing of web services Based on Ontology Management ServiceIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
A review on framework and quality of service based web services discoveryMustafa Algaet
In consequence these services are nowadays accessible to the final clients. In the last few years, more
and more Web Services providing the same functionalities are available in the environment. In order to
select the best service adapted to client’s requests, we need some method capable to evaluate and
compare different services providing the same functionalities. In this context, Quality of service can be defined as the capability to respond to the requirements (constraints) of a client and to fulfill these
needs with the best criteria (preferences) established by the client. It is calculated based on the non-
functional properties of the service. This paper provides an overview of a research progress in Quality
of Service Based Web Services Discovery; it also highlights the issues that need to be investigated in
Quality of Service Based Web Services
SERVICE SELECTION BASED ON DOMINANT ROLE OF THE CHOREOGRAPHYijwscjournal
Web services are playing dominant role on Internet for e-business. The compositions of these services are used to meet business objectives. The web service choreography describes the external observable behavior
of these compositions. Many compositions may available for same functionality. These compositions cannot be distinguished on the basis of functional properties. This Quality of services (QoS) may help the user to select web services and to analyze composition of the web services. Web service choreography is going to dictate implementation of workflow. This workflow consists of several tasks. Each task is implemented by web services. These services are hosted in large numbers by different service providers on different service clusters. The mapping of service and task is difficult issue in run time environment. The interoperability between services is also a great problem. The selection of services is very big issue. In this paper we have proposed a bio-inspired selection algorithm based on dominant role and proposed a discovery infrastructure. We have also used the client behavior to improve the failure of the composition of the service.
FUZZY-BASED ARCHITECTURE TO IMPLEMENT SERVICE SELECTION ADAPTATION STRATEGYijwscjournal
One of the main requirements in service based applications is runtime adaptation to changes that occur in
business, user, environment, and computational contexts. Changes in contexts lead to QOS degrade.
Continues adaptation mechanism and strategies are required to stay service based applications(SBA) in
safe state. In this paper a framework for runtime adaptation in service based application isintroduced. It
checks user requirements change continuously and dynamically adopts architecture model. Also it checks
providers QOS attributes continuously and if adaptation requirement is triggered, runs service selection
adaptation strategy to satisfy user preferences. Thusit is a context aware and automatically adaptable
framework for SBA applications. Wehave implemented a fuzzy based system for web service selection unit.
Due to ambiguity of context’s data and cross-cutting effects of quality of services, using fuzzy would result
an optimised decision. Finally we illustrated that using of it has a good performance for web service based
applications.
A COMPARATIVE STUDY OF PROCESS MEDIATOR COMPONENTS THAT SUPPORT BEHAVIORAL IN...ijwscjournal
The document discusses behavioral incompatibility between web services and process mediation approaches to resolve it. It defines four levels of mismatches - data, functional, protocol, and deadlock - that can cause incompatibility. Process mediation involves generating a mediator service to resolve protocol-level mismatches and enable successful interaction. The paper reviews several state-of-the-art mediation components and approaches, and provides a comparative evaluation based on important criteria like expressiveness, automation, correctness and completeness.
User-Centric Optimization for Constraint Web Service Composition using a Fuzz...ijwscjournal
ABSTRACT
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed
environments. In such systems, however each service responds the user request independently, it is
essential to compose them for delivering a compound value-added service. Since, there may be a number of
compositions to create the requested service, it is important to find one which its properties are close to
user’s desires and meet some non-functional constraints and optimize criteria such as overall cost or
response time. In this paper, a user-centric approach is presented for evaluating the service compositions
which attempts to obtain the user desires. This approach uses fuzzy logic in order to inference based on
quality criteria ranked by user and Genetic Algorithms to optimize the QoS-aware composition problem.
Results show that the Fuzzy-based Genetic algorithm system enables user to participate in the process of
web service composition easier and more efficient.
USER-CENTRIC OPTIMIZATION FOR CONSTRAINT WEB SERVICE COMPOSITION USING A FUZZ...ijwscjournal
This document summarizes a research paper that proposes a user-centric approach for evaluating and optimizing constraint-based web service compositions using fuzzy logic and genetic algorithms. The approach uses fuzzy logic to model user preferences through quality criteria rankings. It then uses a genetic algorithm to optimize the composition process to maximize user satisfaction based on those fuzzy preferences. The results showed that the fuzzy-genetic algorithm system enables users to more easily and efficiently participate in and guide the web service composition process according to their needs and preferences.
MMUNE-INSPIRED METHOD FOR SELECTING THE OPTIMAL SOLUTION IN SEMANTIC WEB SE...dannyijwest
The increasing interest in developing efficient and effective optimization techniques has conducted
researchers to turn their attention towards biology. It has been noticed that biology offers many clues for
designing novel optimization techniques, these approaches exhibit self-organizing capabilities and permit
the reachability of promising solutions without the existence of a central coordinator. In this paper we
handle the problem of dynamic web service composition, by using the clonal selection algorithm. In order
to assess the optimality rate of a given composition, we use the QOS attributes of the services involved in
the workflow as well as, the semantic similarity between these components. The experimental evaluation
shows that the proposed approach has a better performance in comparison with other approaches such as
the genetic algorithm
AN ARCHITECTURE FOR WEB SERVICE SIMILARITY EVALUATION BASED ON THEIR FUNCTION...ijwscjournal
By increasing popularity of SOC, using Web services in applications has increased too. SOC creates a loosely coupled environment in which the actual execution environment might differ significantly from the one with the presupposed conditions during application design. Therefore, although an appropriate Web service might have been selected, by passing time, the Web service may not be efficient enough or may not be applicable under specific conditions.
For service-oriented systems to be flexible and self-adaptive, it is necessary to automatically select and use a similar service instead of the one which causes the above mentioned problems. Finding a similar service means specifying the proper services which fulfill the same requirements as those fulfilled by the problematic service.
In most of the previous works, a number of the best services (k) are selected and ordered based on functional similarity. The user must select one of these services based on his/her preferences. One important metric in selecting a similar service is considering QoS properties and user preferences about QoS. Because of the importance of this issue, in the present paper, an architecture is proposed in which, in addition to functional similarity, QoS properties and user preferences are also considered in selecting a similar service.
AN ARCHITECTURE FOR WEB SERVICE SIMILARITY EVALUATION BASED ON THEIR FUNCTION...ijwscjournal
By increasing popularity of SOC, using Web services in applications has increased too. SOC creates a loosely coupled environment in which the actual execution environment might differ significantly from the one with the presupposed conditions during application design. Therefore, although an appropriate Web service might have been selected, by passing time, the Web service may not be efficient enough or may not be applicable under specific conditions.
For service-oriented systems to be flexible and self-adaptive, it is necessary to automatically select and use a similar service instead of the one which causes the above mentioned problems. Finding a similar service means specifying the proper services which fulfill the same requirements as those fulfilled by the problematic service.
In most of the previous works, a number of the best services (k) are selected and ordered based on functional similarity. The user must select one of these services based on his/her preferences. One important metric in selecting a similar service is considering QoS properties and user preferences about QoS. Because of the importance of this issue, in the present paper, an architecture is proposed in which, in addition to functional similarity, QoS properties and user preferences are also considered in selecting a similar service.
AN ADAPTIVE APPROACH FOR DYNAMIC RECOVERY DECISIONS IN WEB SERVICE COMPOSITIO...ijwscjournal
Service Oriented Architecture facilitates automatic execution and composition of web services in distributed environment. This service composition in the heterogeneous environment may suffer from various kinds of service failures. These failures interrupt the execution of composite web services and lead towards complete system failure. The dynamic recovery decisions of the failed services are dependent on non-functional attributes of the services. In the recent years, various methodologies have been presented to provide recovery decisions based on time related QoS (Quality of Service) factors. These QoS attributes can be categorized further. Our paper categorized these attributes as space and time. In this paper, we have proposed an affinity model to quantify the location affinity for composition of web services. Furthermore, we have also suggested a replication mechanism and algorithm for taking recovery decisions based on time and space based QoS parameters and usage pattern of the services by the user.
QOS Aware Formalized Model for Semantic Web Service SelectionIJwest
Selecting the most relevant Web Service according to a client requirement is an onerous task, as innumerous number of functionally same Web Services(WS) are listed in UDDI registry. WS are functionally same but their Quality and performance varies as per service providers. A web Service Selection Process involves two major points: Recommending the pertinent Web Service and avoiding unjustifiable web service. The deficiency in keyword based searching is that it doesn’t handle the client request accurately as keyword may have ambiguous meaning on different scenarios. UDDI and search engines all are based on keyword search, which are lagging behind on pertinent Web service selection. So the search mechanism must be incorporated with the Semantic behavior of Web Services. In order to strengthen this approach, the proposed model is incorporated with Quality of Services (QoS) based Ranking of semantic web services.
This paper focuses on various concepts of Quality of Service associated with web services. Various QoS parameters like performance, availability, reliability and stability etc. are formalized in order to enhance the pertinence of web service selection. A QoS mediator agent based Web Service Selection Model is proposed where QoS Consultant acts as a Mediator Agent between clients and service providers. Model suggests user’s preferences on QoS parameter selection. The proposed model helps to select pertinent Web Service as per user’s requirement and reduce the human effort.. Further process of adding ontology with semantic web services is also illustrated here.
QOS OF WEB SERVICE: SURVEY ON PERFORMANCE AND SCALABILITYcscpconf
In today’s scenario, most of the organizations provide the services through the web. This makes the web service an important research area. In addition, early design and building web services, it is necessary to concentrate on the quality of web services. Performance is an important quality attributes that to be considered during the designing of web services. The expected
performance can be achieved by proper scheduling of resources and scalability of the system. Scalability is a desirable attribute of a process computer system or network. Poor scalability
can result in lacking system performance. Hence, in this paper, we have reviewed the literature available for the quality attributes of performance and scalability and identified the issues that
affect the quality attributes related to Web Services
An effective method for clustering-based web service recommendationIJECEIAES
Normally web services are classified by the quality of services; however, the term quality is not absolute and defined relatively. The quality of web services is measured or derived using various parameters like reliability, scalability, flexibility, and availability. The limitation of the methods employing these parameters is that sometimes they are producing similar web services in recommendation lists. To address this research problem, the novel improved clustering-based web service recommendation method is proposed in this paper. This approach is mainly dealing with producing diversity in the results of web service recommendations. In this method, functional interest, quality of service (QoS) preference, and diversity features are combined to produce a unique recommendation list of web services to end-users. To produce the unique recommendation results, we propose a varied web service classification order that is clustering-based on web services’ functional relevance such as non-useful pertinence, recorded client intrigue importance, and potential client intrigue significance. Additionally, to further improve the performance of this approach, we designed web service graph construction, an algorithm of various widths clustering. This approach serves to enhance the exceptional quality, that is, the accuracy of web service recommendation outcomes. The performance of this method was implemented and evaluated against existing systems for precision, and f-score performance metrics, using the research datasets.
CHARACTERIZATION OF USER-PERCEIVED QUALITY OF SERVICE (QOS) IN MOBILE DEVICES...ijwmn
This paper presents a user-centric and application-specific QoS assessment methodology for cellular
communication networks. Specifically, it uses the Analytic Hierarchy Process (AHP) to evaluate QoS as a
multi-criteria decision problem that represents how well cellular networks’ data services are perceived
given particular sets of application classes and relative to other networks servicing in the same area. As
part of the methodology, drive testing is performed to collect objective measurements associated with
identified QoS criteria for data services. Once drive testing is performed and data collected, multiple
networks are compared to determine the network that provides higher QoS based on users’ perception of
quality. The selection of the best performing network is based on the output provided by the AHP
approach, which is used as unified measurement of the perceived QoS by users on different networks. In
order to determine application-specific priorities, the approach presented uses three different application
classes, including Emergency, Business, and Personal. For each class, the relative importance of each
quality evaluation criteria is adjusted in the AHP procedure to reflect the priorities of the services
expected. Through several case studies, the approach is proven successful in providing a way for
analyzing user-centric QoS for application-specific scenarios.
Location-Aware and Personalized Collaborative Filtering for Web Service Recom...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Cloud service ranking with an integration of k-means algorithm and decision-m...IJECEIAES
The present research focuses on ranking cloud services by using the k-means algorithm with multi-criteria decision-making (MCDM) approaches that are the prime factor in the decision-making process and have been used to choose cloud services. The tools offered by MCDM can solve almost any decision-making problem. When faced with a selection challenge in the cloud environment, the trusted party would need to weigh the client’s choice against a predetermined list of criteria. There is a wide range of approaches to evaluating the quality of cloud services. The deep learning model has been considered a branch of artificial intelligence that assesses datasets to perform training and testing and makes decisions accordingly. This paper presents a concise overview of MCDM approaches and discusses some of the most commonly used MCDM methods. Also, a model based on deep learning with the k-means algorithm based decision-making trial and evaluation laboratory (kDE-MATEL) and analytic network process (ANP) is proposed as k-means algorithm based decision-making trial and evaluation laboratory with analytic network process (kD-ANP) for selecting cloud services. The proposed model uses the k-means algorithm and gives different levels of priority and weight to a set of criteria. A traditional model is also compared with a proposed model to reflect the efficiency of the proposed approach.
FUZZY-BASED ARCHITECTURE TO IMPLEMENT SERVICE SELECTION ADAPTATION STRATEGYijwscjournal
One of the main requirements in service based applications is runtime adaptation to changes that occur in business, user, environment, and computational contexts. Changes in contexts lead to QOS degrade. Continues adaptation mechanism and strategies are required to stay service based applications(SBA) in safe state. In this paper a framework for runtime adaptation in service based application isintroduced. It checks user requirements change continuously and dynamically adopts architecture model. Also it checks providers QOS attributes continuously and if adaptation requirement is triggered, runs service selection adaptation strategy to satisfy user preferences. Thusit is a context aware and automatically adaptable
framework for SBA applications. Wehave implemented a fuzzy based system for web service selection unit. Due to ambiguity of context’s data and cross-cutting effects of quality of services, using fuzzy would result an optimised decision. Finally we illustrated that using of it has a good performance for web service based applications.
Service selection in service oriented architecture using probabilistic approa...IJECEIAES
In service Oriented Architecture, many services are offered with similar functionality but with different service quality parameters. Thus the service selection using a deterministic approach causes conflicts and inefficient results. We use asynchronous queue to model the service inventory architecture avoiding unnecessary locking of resources and thus allowing a provision to consumers to get their required services without intervening and with temporally decoupled fashion. Actually this kind of service selection strategy is considered in regards with game theory to eliminate fluctuations of queue length. It offers a discrete random service which is equal to some request requested by consumers, it means service can be provided based on probability mass function as a substitute of deterministic decisions for selecting a proper service provider as of the consumers. Once the request is taken out from the queue, it is delivered to the interceptor that has validation and sanitization module. It thus reduces the peak queue length and reduces periodic fluctuations in the queue length.
A Privacy-Preserving QoS Prediction Framework for Web Service RecommendationIRJET Journal
This document discusses a privacy-preserving QoS prediction framework for web service recommendation. It begins with an introduction to web services and the importance of quality of service (QoS) metrics in selecting web services. It then discusses existing recommender system techniques like collaborative filtering for web service recommendation. The document proposes a new technique for predicting QoS values based on known QoS data while preserving privacy. It reviews related work on QoS-aware and location-aware web service recommendation techniques. Finally, it outlines the framework of a proposed location-aware and privacy-preserving QoS prediction approach for web service recommendation.
This document reviews different techniques for selecting web services for web service composition based on quality of service (QoS) requirements. It discusses four main approaches: 1) a composition requirement tree approach, 2) a selection process based on a mediator, 3) selection based on QoS value prediction, and 4) a tool framework for composite web services. It compares these approaches based on factors like what QoS criteria they consider, whether they can handle functionally equivalent and non-equivalent services, and if they utilize databases like UDDI for discovering services. The document concludes that the tool framework approach is best as it leverages UDDI and QoS brokers while also testing services.
AGENTS AND OWL-S BASED SEMANTIC WEB SERVICE DISCOVERY WITH USER PREFERENCE SU...IJwest
Service-oriented computing (SOC) is an interdisciplinary paradigm that revolutionizes the very fabric of
distributed software development applications that adopt service-oriented architectures (SOA) can evolve
during their lifespan and adapt to changing or unpredictable environments more easily. SOA is built
around the concept of Web Services. Although the Web services constitute a revolution in Word Wide Web,
they are always regarded as non-autonomous entities and can be exploited only after their discovery. With
the help of software agents, Web services are becoming more efficient and more dynamic.
The topic of this paper is the development of an agent based approach for Web services discovery and
selection in witch, OWL-S is used to describe Web services, QoS and service customer request. We develop
an efficient semantic service matching which takes into account concepts properties to match concepts in
Web service and service customer request descriptions. Our approach is based on an architecture
composed of four layers: Web service and Request description layer, Functional match layer, QoS
computing layer and Reputation computing layer.
QOS OF WEB SERVICE: SURVEY ON PERFORMANCE AND SCALABILITYcsandit
In today’s scenario, most of the organizations provide the services through the web. This makes
the web service an important research area. In addition, early design and building web services,
it is necessary to concentrate on the quality of web services. Performance is an important
quality attributes that to be considered during the designing of web services. The expected
performance can be achieved by proper scheduling of resources and scalability of the system.
Scalability is a desirable attribute of a process computer system or network. Poor scalability
can result in lacking system performance. Hence, in this paper, we have reviewed the literature
available for the quality attributes of performance and scalability and identified the issues that
affect the quality attributes related to Web Services.
- The document proposes a new approach to decrease the impact of SLA (service level agreement) violations on user satisfaction levels in cloud computing environments.
- It uses two hidden user characteristics - willingness to pay for service and willingness to pay for certainty - to inform a proactive resource allocation approach.
- The goal is to improve user satisfaction and profitability by considering these characteristics, rather than just SLA parameters, when deciding how to allocate resources during critical situations where some SLA violations are unavoidable.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
AI for Legal Research with applications, toolsmahaffeycheryld
AI applications in legal research include rapid document analysis, case law review, and statute interpretation. AI-powered tools can sift through vast legal databases to find relevant precedents and citations, enhancing research accuracy and speed. They assist in legal writing by drafting and proofreading documents. Predictive analytics help foresee case outcomes based on historical data, aiding in strategic decision-making. AI also automates routine tasks like contract review and due diligence, freeing up lawyers to focus on complex legal issues. These applications make legal research more efficient, cost-effective, and accessible.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
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Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
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Software Testing: A Strategic Approach to Software Testing, Strategic Issues, Test Strategies for Conventional Software, Test Strategies for Object -Oriented Software, Validation Testing, System Testing, The Art of Debugging.
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WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATION
1. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
DOI : 10.5121/ijwsc.2012.3101 1
WEB SERVICE SELECTION BASED ON RANKING OF
QOS USING ASSOCIATIVE CLASSIFICATION
Molood Makhlughian1
, Seyyed Mohsen Hashemi2
, Yousef Rastegari3
and Emad
Pejman1
1
Department of Computer Engineering, Islamic Azad University-South Tehran Branch,
Tehran, Iran
{molood.makhlughian, emad.pejman}@gmail.com
2
Dean of Software Engineering and Artificial Intelligence Department, Islamic Azad
University-Science and Research Branch, Tehran, Iran
hashemi@isrup.com
3
Department of Electrical and Computer Engineering, Shahid Beheshti University,
Tehran, Iran
y_rastegari@sbu.ac.ir
ABSTRACT
With the explosive growth of the number of services published over the Internet, it is difficult to select
satisfactory web services among the candidate web services which provide similar functionalities. Quality
of Service (QoS) is considered as the most important non-functional criterion for service selection. But this
criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences.
The similarity measure (outputs–inputs similarity) between concepts based on ontology in an inter-
connected network of semantic Web services involved in a composition can be used as a distinguishing
criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select
services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify
candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an
Associative Classification algorithm and then rank the most qualified candidate services based on their
functional quality through semantic matching. The experimental results show that proposed framework can
satisfy service requesters’ non-functional requirements.
KEYWORDS
Web Service Selection, Quality of Service (QoS), Classification Data Mining & Semantic Web Services
1. INTRODUCTION
Service Oriented Computing (SOC) and its predominant incarnation as Web Services have
emerged as a powerful concept for building software systems [1].
2. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
2
Web service technology offers a potential solution for developing distributed business processes
and applications, which can be accessible via the Internet. Considering the rapid increase of Web
users and the growing complexity of their demands, simple atomic services are inadequate. When
individual Web services are not able to meet complex requirements, SOC provides a flexible
framework for reusing and composing existing web services in order to build value-added
composite services. At first the functionalities required for these complex requirements (namely
the tasks) and their interactions, the control and data flow, are identified. Secondly, an appropriate
implementation must be selected and bounded to each task. However with the rapidly growing
number of available services, a large number of services can be found for realizing every task
which can provide expected functionality for each of them. So it leads to the issue of selecting the
best Web services among a list of “Candidate Web services”, with the same functionalities. These
services are, of course, different from one another in non-functional properties such as response
time, availability, throughput, security, reliability, and execution cost [2], and are therefore
different in terms of efficiency.
A specific issue emerges to this regard is selecting the best set of services based on their Quality
of services (QoS) to participate in the composition, meeting QoS constraints set by users. QoS is
a measure for how well a service serves the customer.
Dynamic service environments cause some difficulties in service selection. As the services’
availability cannot be known a priori, or QoS conditions fluctuate in such environments, service
selection and composition must be performed at runtime. Therefore the execution time of service
selection algorithms is heavily constrained, whereas the computational complexity of the problem
is NP-hard [3]. Hence, finding an optimal composite service may not be practical. Due to
changing conditions in such environments there is no guarantee that the selected services for
composite service will be available at runtime or its QoS will not be fixed concerning the
advertised one in WSDL.
In this paper, we present a service selection algorithm that copes with above issues. This
algorithm consists of two phases. In the first phase, we use a classification data mining algorithm
to classify web service candidates into different QoS levels respect to the defined QoS constraints
form the user and using the result of this classification to define a utility value for each of the
service candidates. In the second phase we focus on composing the best services of each task and
more specifically on their functional level that aims to selecting and inter-connecting web
services by means of their semantic connections.
The remainder of this paper is structured as follows. In the next Section we give an overview of
related works. In Section 3, we present our service selection approach and give the details of it,
and we conduct a set of experiments to evaluate its timeliness and optimality in Section 4.
Finally, in Section 5, we conclude with a summary of our contributions and the future
perspectives of this work.
2. RELATED WORKS
The approaches aim at determining the optimal service composition using brute-force-like
algorithms (i.e., the execution time and costs are exponential even if simplifications are used),
new approaches are satisfied with finding a nearly-optimal solution. These approaches are using
(meta-) heuristics. (Meta-) heuristics are general search methods that exclude a huge number of
solutions, because they do not consider optimal solution in their population. Hence (meta-)
heuristics are more efficient than exact algorithms. The main disadvantage however is that they
do not find the optimal solution in most cases, because, the exclusion of solutions is based on
3. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
3
assumptions, thus there is no guarantee, that the excluded solutions do not contain the optimal
one.
All existing approaches can be divided into exact approaches finding the optimal service
composition and (meta-) heuristics selecting a nearly service composition. Instead of exact
algorithms, (meta-) heuristics seem to be the better choice for QoS-aware service selection and
composition.
Beside many proprietary heuristics [4,5,6], currently the Genetic Algorithm is the most promising
heuristic in QoS-aware service selection and composition. C. Jaeger et al. [7] present a heuristic
based on the genetic algorithm. A big challenge related to the Genetic Algorithms is the choice of
the genetic operators: selection, mutation and recombination, which have a big influence of the
efficiency and correctness of the algorithm. As these parameters are chosen randomly, the order
in which service candidates are checked is chosen randomly. On the other hand, as the genetic
algorithm can run endlessly, the users have to define a constant number of iterations fixed a
priori, and fixing a high number of iterations does not give any guarantee about the quality of the
result. Therefore, the genetic algorithm is deemed not useful for the purpose of selecting near-
optimal compositions.
In recent years, some approaches (e.g., [8,9]) use the power of Data mining algorithms in
knowledge extraction and pattern discovery among the huge amounts of data in web service
selection.
Wu et al. [8] present a Bayesian network based Qos assessment model for web services. That
could predict the service capability in various combinations of users’ Qos requirements. This
approach is used to evaluate the capability of each service, and the one with best capability is
selected as the binding service. Though it uses Bayesian network classification algorithm for each
provider/service to predict the level of QoS, it is computationally complex and is based on
probabilities, moreover it just considers local constraints in web service selection and doesn’t
mention the global constraints.
Ben Mabrouk et al. [9] present a heuristic approach for service composition in dynamic
environments. This solution uses the K-means algorithm to classify the web services to QoS
levels, then it uses the result of this clustering in an utility function in order to rank web service
candidates for each task as a local selection part, then it uses a search tree to select the best
services to form the composition plans in an ordered way. The proposed solution is
computationally expensive in both of the clustering algorithm and the structure of the search tree
in a composition plans with the high number of activities, also it suffers from the deficiency of
the clustering techniques, because clustering is an example of unsupervised learning. Furthermore
it does not mention the semantic matching between output and input of the services.
3. QOS-AWARE SERVICE SELECTION ALGORITHM
Our proposed approach starts form the assumption that the user uses a graphical user interface to
define his/her request. With the help of this interface user can express his request in terms of QoS
requirements and his relative preferences for each of them. Then the interface formulates it as a
machine-understandable specification. The composition plan is given from the expert that its
functional tasks and all the controls and data flow between them are characterized. For every
activity in the composition plan, a service discovery phase gives a set of service candidates able
to fulfill the functional aspect.
4. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
4
The proposed service selection method consists of a heuristic algorithm based on classification
data mining algorithm, CBA [10] algorithm. This classification allows for classifying candidate
web services with respect to the QoS requirements and preferences defined by the user into a set
of different QoS levels. Further with considering the functional aspect we use these levels to
determine the utility of each candidate service to do a near-optimal selection.
As the outlined process of the proposed method is depicted in figure 1, our heuristic approach
deals with the service selection problem through the following phases:
1. Scaling phase, which is a pre-processing phase to normalizing QoS values.
2. Service selection by local classification, which classifies candidate services according to
different QoS levels and determines the utility of each candidate service.
3. Ranking based on functional aspect, which uses the results of the last phase to selecting
the best services according to the functional aspect.
Figure 1. The outlined process of the proposed method
5. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
5
3.1. Scaling Phase
QoS attributes could be either positive or negative, thus some QoS values need to be maximized,
(i.e., the higher the value, the higher the quality) for example availability and reliability, whereas
other values have to be minimized, (i.e., the higher the value, the lower the quality). This includes
criteria such as execution time and execution price. To cope with this issue, the scaling phase
normalizes every QoS attribute value according to the following formulas [11]. The values of
negative attributes are normalized by expression (1) and the values of positive attributes are
normalized by (2).
ܳ,
ᇱ
= ൝
ொೕ
ೌೣ
ିொ,ೕ
ொೕ
ೌೣ
ିொೕ
, ݂݅ ܳ
௫
− ܳ
≠ 0
1, ݈݁݁ݏ
(1)
ܳ,
ᇱ
= ቐ
ொ,ೕିொೕ
ொೕ
ೌೣ
ିொೕ
, ݂݅ ܳ
௫
− ܳ
≠ 0
1, ݈݁݁ݏ
(2)
Where ܳ,
ᇱ
signifies the normalized value of QoS attribute j associated with candidate service ܵ.
It is computed using the current value ܳ, and ܳ
௫
and ܳ
which respectively denote the
maximum and minimum values of QoS attribute j among all the candidate services.
After the data normalization is completed, all the QoS attributes values are lying in the [0, 1]
interval and also have the same utility increase direction.
3.2. Service Selection by Local Classification
The classification is performed on candidate web services for all the activities in the abstract
service composition. The purpose of this phase is to classify candidate web services to the
multiple QoS levels with respect to the user’s preferences on QoS attributes. In this classification
each level consists of a set of candidate services that have approximately the same QoS value.
These levels determine the relative importance of candidate services for selecting near-optimal
compositions. To perform this classification we use an Associative Classification technique, CBA
algorithm.
3.2.1. Classification Overview
CBA algorithm is based on Associative Classification which is the integration of two important
data mining techniques, Classification rule mining and association rule mining. Associative
Classification is a novel strategy performing classification where model of classification is based
on a set of association rules in which consequent of each rule is restricted to contain only class
attribute values.
Some definitions of associative classification are introduced here:
Definition 1 (Training Data Set .)ܦ If an object can be described by features ܣଵ, ܣଶ, ܣଷ, . , ܣ and
each object belongs to some class in a finite set of classes ,ܥ then training data set ܦ is a
collection of instances < ݒଵ, ݒଶ, ݒଷ, . , ݒ, ܿ > where ݒ ranges over the domain of feature vector
ܣ and ܿ represents the class of the object. As a preprocessing step any continuous valued
attribute need be discretized.
6. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
6
Definition 2 (Future Object ܱ). An instance < ݒଵ, ݒଶ, ݒଷ, . , ݒ > whose class label is not known
will be called future object and classifier will be used to predict its class.
Definition 3 (Class Association Rules: CARs). CARs will be mined from Training data set .ܦ A
special subset of association rules in which the precedent of rule contains the form of attribute
value pairs and the consequent is restricted to take only class attribute value. Like association
rules, CARs are also subjected to a minimum support and confidence threshold values. For
instance a rule ,ݎ ܣ ݒଵ, ܣ ݒଶ, … ! ܿ is a CAR and supp(,)ݎ conf()ݎ respectively denote support
and confidence of rule.
CBA algorithm is an ordered rule algorithm based on coverage analysis. It consists of two parts
Rule Generator and Classifier Builder. The goal of rule generator part is to mine all CARs from ܦ
that their support and confidence are above minimum threshold values. Rule generation approach
is based on Apriori [12]. Classifier builder uses class association rules (CARs). The goal is to
short list high confidence rules from CARs to form a classifier. CARs are sorted in the
descending order of their precedence. We call this set of CARs ܴ. To build the classifier we select
high precedence rules ݎ in ܴ to cover .ܦ Finally classifier takes the form
< ݎଵ, ݎଶ, ݎଷ, . , ݎ, ݂݀݁ܽݏݏ݈ܽܿ_ݐ݈ݑ >. ݂݀݁ܽݏݏ݈ܽܿ_ݐ݈ݑ is the most probable class for all items. If all
rules in the classifier are unable to classify a future object then it will be classified according to
default class.
3.2.2. Defining QoS Levels
In order to classify candidate services, first we need to determine the QoS levels. To this regard
we define ݊ QoS levels, where the value of ݊ is defined with respect to the service density and the
expected accuracy for producing service classes.
Further the training data set is defined by the expert and the number of classes is the number of
QoS levels and the attributes are requested QoS attributes defined by the user.
Each class defines the attributes which their values have a defined distance from the range of the
values that specified from the user’s request. (i.e., the first class shows the services which the
value of their QoS attributes are in the same range with the user’s demand and the second class
shows the services which the value of their QoS attributes are one level lower than the user’s
demand and so on).
3.2.3. Computing the Service Utilities
The objective of our proposed algorithm is selecting the best services for the near-optimal
compositions. Indeed, having a large number of choices for services during dynamic binding
increases the number of alternative service compositions and subsequently a large number of
compositions prevent the starvation in dynamic service environments.
In this regard, we define a utility function ܷ which shows the relative importance of a candidate
service ܵ. This function is computed based on two parameters: the first one is the QoS level
which the service is classified in it through the classification, it represents the importance of the
service (i.e., if it belongs to a class that its attributes are closer to the user demands, it will be
better choice for selecting). The second one is the overall quality of the service. Concerning to
this parameter, the service with the higher quality has the higher ability to be selected.
This function is computed as follows:
7. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
7
ܷ = ݏݏ݈ܽܥ ∗ ݁ݒܣ Where ݁ݒܣ =
∑ ொ,ೕ
ᇲ
ೕసభ
(3)
Where ݏݏ݈ܽܥ is the coefficient of the class to which service ܵ belongs. ݁ݒܣ is the total quality
of service ܵ, which computed as the average of the normalized QoS attributes values.
3.3. Ranking Based on Functional Aspect
The aim of this phase is selecting the best services for the near-optimal compositions such that 1)
consider the best quality regard to the user’s demand and 2) the composition of these services has
high functionality.
3.3.1. Considering the Most Eligible Services
In order to select services for the near-optimal compositions we use the utility function that we
have computed from the result of the classification part. So we do not consider all the possible
combinations of services. In this regard, we just mention the candidate services that have a utility
value over a defined threshold. This threshold allows us to focus on the most qualified services to
our regard.
For defining threshold we consider two aspects: the number of required compositions and the
execution time of the algorithm. Indeed, if we decrease the value of this threshold, the number of
considered candidate services decreases. Consequently, the number of compositions and the
execution time of the algorithm decreases respectively. Tuning the trade-off between these two
aspects will make our algorithm adaptable; hence it could be applied to multiple dynamic service
environments according to their constraints.
3.3.2. Functional Aspect of the Composition
Unlike most of approaches which just focus on the quality of composition by means of non
functional parameters (i.e. QoSs), the quality of semantic links can be considered as a
distinguishing functional criterion for semantic web service compositions.
Here we focus on the functional level of composing the candidate web services. The functional
criteria of semantic link, was introduced for the first time in [13] which defined as a semantic
connection between an output of a service and an input parameter of another service. Since the
qualities of these connections are valued by a semantic matching between their parameters,
semantic link composition could be estimated and ranked as well. Through the results of these
estimations some compositions are inappropriate. Indeed a composite service which does not
provide acceptable quality of semantic links might be useless as a service that does not provide
the desired functionality. Indeed the semantic connection between Web services is considered as
essential to form new value-added Web services.
Here we address the problem of optimizing in service selection with respect to this functional
criterion. In other words, we focus on the aspects of selecting a set of appropriate service
candidates for each task. We define an objective function In order to consider this aspect,
preferences and constraints which are defined by end-user.
3.3.2.1. Semantic Links
In semantic web, input and output parameters of web services are concepts referred to an
ontology ܶ, where the OWL-S profile [14], SA-WSDL [15] or WSMO capability [16] can be
used to describe them (through semantic annotations).
8. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
8
At functional level, web service composition consists of retrieving some semantic links between
output parameters ܱݏ_ݐݑ ∈ ܶ of service ݏ and input parameters ݏ_݊ܫ ∈ ܶ of other service ݏ.
Such a link i.e., semantic link, ݈ݏ, (Figure 2) between two functional parameters of ݏ and ݏ is
formalized as 〈ݏ, ்ܵ݅݉൫ܱݏ_ݐݑ, ݏ_݊ܫ൯, ݏ〉. Thereby ݏ and ݏ are partially linked according to a
matching function ்ܵ݅݉. This function expresses which matching type is employed to chain
services.
The range of ்ܵ݅݉ is reduced to the four well known matching types:
• Exact If the output parameter ܱݏ_ݐݑ of ݏ and the input parameter ݏ_݊ܫ of ݏ are
equivalent; formally, ܶ ⊨ ܱݏ_ݐݑ ≡ ݏ_݊ܫ.
• PlugIn If ܱݏ_ݐݑ is sub-concept of ݏ_݊ܫ; formally, ܶ ⊨ ܱݏ_ݐݑ ⊆ ݏ_݊ܫ.
• Subsume If ܱݏ_ݐݑ is super-concept of ݏ_݊ܫ; formally, ܶ ⊨ ݏ_݊ܫ ⊆ ܱݏ_ݐݑ.
• Intersection If the intersection of ܱݏ_ݐݑ and ݏ_݊ܫ is satisfiable; formally, ܶ ⊭
ܱݏ_ݐݑ ⊓ ݏ_݊ܫ ⊆ ⏊.
• Disjoint Otherwise ܱݏ_ݐݑ and ݏ_݊ܫ are incompatible i.e., ܶ ⊨ ܱݏ_ݐݑ ⊓ ݏ_݊ܫ ⊆ ⏊.
Figure 2. A Semantic Link ݈ݏ, between ݏ, ݏ.
3.3.2.2. Semantic Link Quality
Several candidate services are grouped together in every task of an abstract composition. A
method to differentiate their semantic links is to consider their different functional quality criteria.
In this way, we use the semantic link quality model introduced in [17].
Here We consider the matching quality as the quality criteria for the semantic links ݈ݏ, defined
by 〈ݏ, ்ܵ݅݉൫ܱݏ_ݐݑ, ݏ_݊ܫ൯, ݏ〉. The Matching Quality ݍ of a link ݈ݏ, is a value in (0, 1]
defined by ்ܵ݅݉൫ܱݏ_ݐݑ, ݏ_݊ܫ൯ i.e., 1 for Exact matching type,
ଷ
ସ
for PlugIn,
ଵ
ଶ
for Subsume and
ଵ
ସ
for Intersection.
The Disjoint match type is not considered since ܱݏ_ݐݑ ⊓ ݏ_݊ܫ is satisfied.
Given the above quality criteria, the quality vector of a semantic link ݈ݏ, is defined as follows:
ݍ൫݈ݏ,൯ = ቀݍ൫݈ݏ,൯ቁ (4)
In case of services ݏ and ݏ related by more than one semantic link, the value of each criterion is
retrieved by computing their average.
9. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
9
3.3.2.3. Generation of the Search Graph
Our algorithm uses the structure of a graph for selecting the most appropriate candidate services
for the composition. Moreover in this graph we use a priority queue to exploring the candidate
services in a defined order corresponding to their importance of QoSs and semantic similarities
with other services. These priority queues reduce the time spend for building and traversing the
search graph by inclusion the unexplored candidate services in themselves. In addition they can
increase the speed of search to acquiring the optimal composite services according to their
importance, by visiting the first services of each queue. Hence this structure will decrease the
computational complexity of traversing the graph and memory usage in the cases which the
abstract service compositions comprises a large number of tasks or there are many candidate
services for each task.
This graph is built from the candidate services according to the following rules:
• Each node represent a task in the abstract service composition;
• The order of these nodes is the corresponding order in the composition plan (i.e., if there
is a link from task ܶ௫ to ܶ௬ in the abstract service composition, then the corresponding
node of ܶ௬ will be after the corresponding node of ܶ௫);
• These nodes are made of a priority queue which consists of all the service candidates for
the corresponding task which its ܷ is above the defined threshold as we have introduced
before;
Candidate services for each task go to the priority queue in this order:
• For the tasks which do not have any incoming task in the composition plan, web services
stay in the queue based on their utility values, i.e. the service with the highest utility value
(ܷ) stays at the top of the queue;
• For the other tasks, web services stay in the queue based on the following formula:
ܨ = ܷ ∗ ݍ൫݈ݏ,൯ (5)
Where ܨ is the final utility value for each candidate service based on their QoS values
that respects the user needs and the matching quality of their semantic links between
them and their preceding service;
To build the search graph, first of all we add the nodes correspond to the tasks which do not have
any incoming task. Then we select a web service which is at the top of its queue. To select the
services for the other nodes, we compute the matching quality of semantic links between the
selected services and all the candidate services for the subsequent nodes then based on these
values and the utility values (which was computed in the local selection part), stay the candidate
services for these nodes in the priority queue based on their ܨ values. As the previous nodes, the
service which is top of the queue is selected as the chosen service. And so on the other services
for each node will have selected which the candidate services of each node stay in their
corresponding queue based on the value of their ܨ.
The selected services from top of the queues form the near-optimal composite service. This
composite service is the first service that have the highest importance and unexplored services in
each queue are the candidates for alternative composite services which when the services in the
first composite service are no longer available or their QoS decreases (e.g., due to network
disconnection or weak network connectivity) during the execution of the composition, could be
replace with it.
10. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
10
The introduced structure of the search graph, allow for producing all the alternative composite
services by selecting the unexplored candidate services in each queue. But on the other side,
producing all the alternative composite services needs more computation so it is a time
consuming process (for calculating semantic similarities between services), also saving these
composite services need high memory, hence for tuning the trade-off between memory usage and
the execution time of the algorithm, we produce only the first alternative composite service which
is the best alternative.
We also propose a method for the case when a service which takes part in the composite service
is no longer available, we could propose another composite service by replacing the unavailable
service with another candidate service in its corresponding node of the search graph. In this case,
for switching to another composite service we must rearrange the priority queue in that
corresponding node, based on new utility values. This utility value is as the same as the ܨ
function but the quality of the semantic links will be calculated as the follow:
At first we calculate the semantic quality of the connection between the selected service in the
previous node with the services for this node and the semantic quality of the connection between
the selected service in the following node with the services for this node, then the new semantic
quality value for the new ܨ is computed based on the average of these two computed quality for
each service in this node.
4. EXPERIMENTAL EVALUATION
4.1. Experimental Settings
We conducted experiments on an Intel(R) Core(TM) Duo CPU, 2.53GHz, 4GB RAM and a
windows 7 operating system. In this experiment we focus on the execution time of our method.
This metric measures the response time of our algorithm with respect to the size of the problem in
terms of the number of activities and the number of services per activity. In these experiments, we
measure the execution time of the ranking phase.
For the quantity allocation of the service qualitative parameters we use the QWS real dataset [18,
19]. This dataset includes measurements of 9 QoS attributes for 2500 real web services. The
dataset was measured using commercial benchmark tools for web services, which were located
using public sources on the Web, including UDDI registries, search engines and service portals.
In these studies, the authors provide a set of QoS metrics (i.e., response time, throughput,
availability, validation accuracy, reliability). We use these metrics as a sample input data for our
algorithm.
To accomplish the classification, we used the CBA1
tool for implementing the classification
algorithm. This tool has a graphical user interface and is designed particularly for implementing
the CBA algorithm. Hence for this part we do not measure the response time.
For classifying the candidate services we have defined 3 different quality levels. These levels are
specified to the distance of the QoS attributes to the user demands.
After the classification carried out, the classes’ coefficient were defined as follow: 1 for services
in the first class,
ଷ
ସ
for services in the second class and
ଵ
ସ
for services in the third class.
In general, on Contrary to QoS given by providers, the quality of semantic links are estimated
according to DL reasoning. Matching quality of each semantic link has been inferred in a pre-
1
http://www.comp.nus.edu.sg/~dm2/
11. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
11
processing step of semantic reasoning. Standard DL reasoning inference is achieved by means of
a DL reasoner Fact++2
[20].
For the purpose of these experiments, we vary the number of activities and the number of services
per activity between 10 and 50. The number of QoS constraints is fixed to 4 constraints (i.e.,
Response time, Availability, Throughput and Reliability) and for the sake of precision each
experiment is executed 20 times and finally we calculate the mean value of the obtained results
for our evaluation.
4.2. Performance Results
In figure 3 we demonstrate the execution time of ranking phase for the calculated near-optimal
composite service. These measurements are obtained by fixing the number of QoS constraints to
4 and varying the number of activities and the number of service candidates per activity between
10 and 50. The obtained measurements show that the execution time of our algorithm increases
along with the number of activities and the number of services per activity, which is an expected
result.
Figure 3. Execution time of the ranking phase for near-optimal composite service
Also figure 4 demonstrates the execution time of ranking phase for the first alternative composite
service. The increment of the execution time compared with the figure 3 is due to the increment
of the number of tasks and candidate services so the spending time for calculating semantic
similarity of output-input concepts increases subsequently. DL reasoning is the most time
consuming process in large-scale problem of quality-driven semantic web service composition
(i.e., number of tasks and candidate services greater than 100 and 350).This is caused by the large
number of potential semantic links between tasks.
2
http://owl.man.ac.uk/factplusplus/
12. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
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Figure 4. Execution time of the ranking phase for first alternative composite service
As the figure 3 and 4 show, our method has a good execution time compared with the
evolutionary algorithms which the later algorithms (e.g., genetic algorithms, PSO) take a long
time to execute composite service (e.g., for a number of activities more than 25, it takes 2847 and
2236 ms, respectively for the PSO and GA algorithms [21]).
Moreover unlike our proposed method which aims to produce the composite services in an
ordered way, the evolutionary algorithms produce the composite services in an unordered way
and there is no evidence that the first composite service which produced by these algorithms be
the optimal one, in other words the next produced composite services may be better than the first
one.
5. CONCLUSION
As the number of the services published over the internet is growing at a very fast pace, selecting
satisfactory web services among the candidate web services which provide the same
functionalities is difficult. QoS is considered as the most important non-functional criterion for
further filtering services. Besides this criterion, the quality of semantic links can be considered as
a distinguishing functional criterion for semantic web service selection and composition.
We address the web service selection problem by defining constraints within a quality model to
balance QoS metric with functional quality. The functional quality evaluates the quality of
semantic links between the semantic description of output-input parameters of web services,
while QoS focuses on the non-functional criterion to retrieve the satisfactory services regard to
the user’s requirements and preferences.
Our objective has been to address service selection in the context of a QoS-aware middleware for
dynamic service environments. To do so we have proposed an approach which at first by using
the CBA algorithm, aims to classify the candidate web services to different QoS levels,
differentiate the services within each class, respect to their distances from the user’s demand for
the QoS criterion. By this classification a utility value is defined for each service that shows its
relative importance. In the next part, by the use of the structure of a graph, we have ranked the
candidate services by defining the final utility of each service considering the results of the
classification phase and their functional quality through measuring the semantic similarity
13. International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 2012
13
between their output-input concepts. Finally by producing alternative composite services in an
ordered way, we could cope with changing conditions of dynamic service environments.
Our proposed approach has four advantages: First, it uses the classification data mining algorithm
to specify the most eligible services respect to the user demand. Applying data mining algorithms
to this field brings new ideas. Second, by producing alternative composite services satisfying QoS
constraints, our algorithm could cope with changing conditions in dynamic service environments.
Third it shows a satisfying capability in terms of execution time, which it is an important point in
dynamic service environments and finally with applying the semantic similarity between services
by semantic links it increases the accuracy of selection.
Our proposed method makes part of our ongoing research by using strong data mining algorithm
in order to decrease the execution time and improve the optimality of our heuristic algorithm, and
besides the local optimization, by combining the global constraint of the user to the local
constraints, considering the QoS constraints through the whole composition to ensure meeting
global QoS constraints.
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Authors
M. Makhlughian received her B.Sc. degree in Software Engineering, from the Azad
University-Parand Branch, Tehran, Iran in 2009 and her M.Sc. degree in Software
Engineering from the Azad University-South Tehran Branch, Tehran, Iran in 2012. Her
research interests include Web Service technology, Service-Oriented Computing, Service
Annotation, Selection and Composition, Ontology Engineering and Data Mining.
Dr. S. M. Hashemi received his M.S. degree in Computer Science from Amirkabir
University of Technology (Tehran Polytechnic University) in 2003, and his PhD degree in
Computer Science from the Azad University in 2009. Moreover, he is currently a faculty
member at Science and Research Branch, Azad University, Tehran. His current research
interests include Software Intensive Systems, E-X systems (E-Commerce, E-Government,
E-Business, and so on), Global Village Services, Grid Computing, IBM SSME, Business
Modelling, Agile Enterprise Architecting through ISRUP, and Globalization Governance
through IT/IS Services.
Y. Rastegari is PhD. Candidate of Computer Engineering Department of Shahid
Beheshti University (SBU) in Tehran, Iran. He is also member of Automated Software
Engineering Research Group (ASER) and Information System Architecture Research
Center at SBU. His research interests include Service Oriented Architecture, Software
Architecture, Software Product Line and Ontology Engineering. He is working on
Service Choreography Adaptation challenge for Collaborative Business Processes.
E. Pejman received his B.Sc. degree in Computer Science and Software Engineering
from the Yazd University, Yazd, Iran in 2009 and his M.Sc. degree in Computer Science
and Software Engineering from the Azad University-South Tehran Branch, Tehran, Iran
in 2012. His research interests include web services, QoS-based service composition,
robotics and image processing.