Towards Service Selective Optimizing Based on Key Business Process Performance

Web service composition has been recognized as a flexible way for resource sharing and application integration. For Web services providing similar functionality, quality of service (QoS) is the main factor to differentiate them. In this paper, the issue of QoS driven service selection in dynamic Web service composition is investigated. OWL-S is extended with a flexible QoS model to better facilitate service selection process. Based on different global constraints users set, the QoS-based service selection problems for composite services are divided into three categories. For each category, the mathematical model and its corresponding solving algorithm are put forward separately. Simulation experiments are conducted to show the validity and efficiency of the algorithms.

Quality of Service (QoS) has been widely used to support dynamic Web Service (WS) selection and composition. Due to the volatile nature of QoS parameters, QoS prediction has been put forward to understand the trend of QoS data volatility and estimate QoS values in dynamic environments. In order to provide adaptive and effective QoS prediction, we propose a WS QoS prediction approach, named WS-QoSP, based on the technique of forecast combination. Different from the existing QoS prediction approaches that choose a most feasible forecasting model and predict relying on this "best" model, WS-QoSP selects multiple potential forecasting models, combines the results of the selected models to optimize the overall forecast accuracy. Results of real data experiments demonstrate the diversified forecast accuracy gains by using WS-QoSP.

While Web service models become increasingly popular and many service providers start to offer all kinds of Web services, the quality of service (QoS) for Web services has become an important factor for service requesters to consider during the selection process of appropriate Web services. In this paper, we present an evaluation and selection framework (CosmosQoS) for QoS-required Web services. A novel architecture and reputation appraisal model to monitor, store and evaluate the physical usage and post-condition of requested Web services in a requester-located network is proposed to better support service requesters such that they can select suitable Web services based on their QoS requirements, trustworthiness of Web services, and effect of network connection and configuration between service requesters and providers.

Research on dynamic business composition based on web service proxies

With the proliferation of Web services as a business solution to enterprise application integration, ranking and selecting the best Web services among the providers become an important factor in the success of the business solution. Quality of service (QoS) determines the quality and usability of a service including its price, performance, reliability, integrity, accessibility, availability, interoperability, and security. Given a set of QoS attributes from a variety of sources, it is a challenge to sort through all of them and be able to get the best services that meet QoS requirement. In this paper, we describe a novel method by which Web services can be ranked and selected automatically based on a number of observed QoS parameters and feedback responses learned from prior knowledge. This new approach treats the observed Web services QoS attributes and target Web services relationship, represented by a matrix, as a statistical problem. Using singular value decomposition (SVD) technique, and an user assisted weighting system, implicit higher order correlations among Web services and their associated QoS attributes are extracted and used to estimate the selection of recommended Web services.

A web service is an interface of the software component that can be accessed by standard Internet protocols. The web service technology enables an application to application communication and interoperability. The increasing number of web service providers throughout the globe have produced numerous web services providing the same or similar functionality. This necessitates the use of tools and techniques to search the suitable services available over the Web. UDDI (universal description, discovery and integration) is the first initiative to find the suitable web services based on the requester's functional demands. However, the requester's requirements may also include non-functional aspects like quality of service (QoS). In this paper, the authors define a QoS model for QoS aware and business driven web service publishing and selection. The authors propose a QoS requirement format for the requesters, to specify their complex demands on QoS for the web service selection. The authors define a tree structure called quality constraint tree (QCT) to represent the requester's variety of requirements on QoS properties having varied preferences. The paper proposes a QoS broker based architecture for web service selection, which facilitates the requesters to specify their QoS requirements to select qualitatively optimal web service. A web service selection algorithm is presented, which ranks the functionally similar web services based on the degree of satisfaction of the requester's QoS requirements and preferences. The paper defines web service provider qualities to distinguish qualitatively competitive web services. The paper also presents the modelling and selection mechanism for the requester's alternative constraints defined on the QoS. The authors implement the QoS broker based system to prove the correctness of the proposed web service selection mechanism.

The increasing proliferation of independent application service providers is making traditional IT infrastructure insufficient when dealing with new issues that appear in a dynamic outsourcing business model. Quality of service (QoS) gradually becomes an essential benchmark to differentiate diverse service providers during service selection process. In this paper, we argue service selection can be deemed as a decision making process -to decide which services providers should be selected within the specified service provision context during a definitive timeslot. Thus, existing decision support approaches can be leveraged if applicable. Hence, we propose a service selection solution which utilizes the decision support systems module (DSS Module) to select the most appropriate service. In DSS module we introduce AHP model to carry out the service QoS measurement based on the Context-specific Quality Aspects. The contributions of this paper are two folds. Firstly, we provide a novel and feasible solution for QoS-based service selection and secondly, we apply DSS module into web services, thus opening a new, fertile ground for DSS research in service ecosystem literature.

Privacy preserving service selection using fully homomorphic encryption scheme on untrusted cloud service platform

Aiming at the hot and difficult issues in Web services and service composition, this paper analyzes and studies the selection of Web services and service composition from the functional and non functional attributes of Web services, and mainly makes the following work and innovation. First of all, the functional attributes of Web services are studied, Web services on various service provision platforms are collected, and Web services are classified. Secondly, aiming at the shortcomings of existing Web service QoS attribute evaluation models, an improved method is proposed, which introduces a comprehensive evaluation mechanism of variable weight vector. Based on the constant weight comprehensive evaluation method, the state variable weight vector is established to dynamically adjust the attribute weights of various service QoS indicators, so as to improve the accuracy and objectivity of the Web service QoS attribute evaluation. Finally, in view of the defects and deficiencies of traditional algorithms in the selection of Web service composition, the particle swarm optimization algorithm with linearly decreasing inertia weight and learning factor is introduced, which better balances the self cognition and social learning ability of particles, and improves the search speed and global search ability of particles. And a large number of experiments are carried out to compare it with the traditional algorithm, which verifies the effectiveness and superiority of the improved particle swarm optimization algorithm.

In the Web Service Composition (WSC) domain, Web Services (WSs) execute in a highly dynamic environment, as a result, the Quality of Service (QoS) of a WS is constantly evolving, and this requires tracking of the global optimization overtime to satisfy the users’ requirements. In order to make a WSC adapt to such QoS changes of WSs, we propose a self-healing model for WSC. Self-healing is the automatic discovery, and healing of the failure of a composite WS by itself due to QoS changes without interruption in the WSC and any human intervention. To the best of our knowledge, almost all the existing self-healing models in this domain substitute the faulty WS with an equivalent one without paying attention to the WS selection processes to achieve global optimization. They focus only on the WS substitution strategy. In this paper, we propose a self-healing model where we use our hybrid approach to find the optimal WSC by using Parallel Genetic Algorithm based on Q-learning, which we integrate with K-means clustering (PGAQK). The components of this model are organized according to IBM’s Monitor, Analyse, Plan, Execute, and Knowledge (MAPE-K) reference model. The PGAQK approach considers as a module in the Execute component. WS substitution strategy has also been applied in this model that substitutes the faulty WS with another equivalent one from a list of candidate WSs by using the K-means clustering technique. K-means clustering is used to prune the WSs in the search space to find the best WSs for the environment changes. We implemented this model over the NET Framework using C# programming language. A series of comparable experiments showed that the proposed model outperforms improved GA to achieve global optimization. Our proposed model also can dynamically substitute the faulty WSs with other equivalent ones in a time-efficient manner

With the development of Internet and Web service technology, Web service composition has been an effective way to construct software applications; service selection is the crucial element in the composition process. However, the existing selection methods mostly generate static plans since they neglect the inherent stochastic and dynamic nature of Web services. As a result, Web service composition often inevitably terminates with failure. An indeterminacy-aware service selection algorithmbased on an improved Markov decision process (IMDP) has been designed for reliable service composition, but it suffers from higher computation complexity. Therefore, an efficient method is proposed, which can reduce the computation cost by converting the service selection problem based on IMDP into solving a nonhomogeneous linear equation set. Experimental results demonstrate the success rate of service composition has been improved greatly, whilst also reducing computation cost.

In the service oriented paradigm applications are created as a composition of independently developed Web services. Since the same service may be offered by different providers with different non-functional Quality of Service (QoS) attributes, a selection process is needed to identify the constituent services for a given composite service that best meet the users QoS requirements. In this paper, we consider a broker that offers a composite service with multiple QoS classes to several users each generating a flow of requests over time. We propose a service selection scheme which optimizes the end-to-end aggregated QoS of all incoming flows of requests by means of a simple linear programming problem which scales as the number of users, request volumes and/or services grows. This approach differs from most of the current proposals which may not scale well since: a) requests, even from the same user, are handled independently from one another; and b) the selection process often requires the solution of an NP-hard problem.

Virtual enterprise is a temporary network of independent companies or enterprises that can quickly bring together to fulfill a value-added task. With the development of Web service technologies, the enterprise business systems can be encapsulated as Web services. Establishing a virtual enterprise is actually a process of Web services composition. As more and more Web services are available, many Web services with different quality of service (QoS) can be found for tasks of the composite Web service. Thus, a significant research problem in Web service composition is how to select the correct Web services for tasks such that the composite Web service gives the best overall quality. In this paper, we propose an approach to achieve Web services selection efficiently with excellent comprehensive quality. Firstly, a comprehensive evaluation model based on generic QoS (GQoS) and domain QoS (DQoS) of composite Web service is established. Secondly, a novel optimization algorithm named culture max–min ant system (C-MMAS) is constructed to solve the problem of Web service selection based on DGQoS. Simulations show that when used in Web service selection, C-MMAS is better than ant colony optimization algorithm and MMAS in efficiency.

With the rapid development of e-commerce over Internet, web services have attracted much attention in recent years. Nowadays, enterprises are able to outsource their internal business processes as services and make them accessible via the Web. Then they can dynamically combine individual services to provide new value-added services. With the increasing number of web services having equivalent functionality, the binding procedure is driven by some non-functional, Quality of Service (QoS) criteria, such as the money cost, response time, reputation, reliability or a trade-off between them. Thus, an important problem is, given QoS constraints, how to aggregate and leverage individual service’s QoS information to derive the optimal QoS of the composite service. In this paper, we propose a novel QoS model for performing flexible service selection. The key idea of the model is to relax users’ QoS constraints and try to find the most possible services satisfying users’ QoS requirements. Based on the proposed QoS framework, we develop various algorithms for making service selection on individual and composite services. We also introduce a top-k ranking strategy to reflect a user’s personalized requirements. Experimental evaluation shows the proposed QoS model is efficient and practical.

With the development of web service, web service composition is used widely. How to guarantee the non-functional requirement of users under the precondition of satisfying functional requirement of users is an important problem in web service composition. To address this problem, this paper presents a web service composition selection approach based on multi-dimension quality of service(QoS) which introduces multi-dimension QoS to describe the QoS of web service composition and computes the QoS of web service composition according to the type of web service composition. Then the web service composition which can best satisfy the non-functional requirement of users can be found from the web service compositions which can satisfy functional requirement of users according to this approach. At last, an application example is used to explain this approach.