Composite Service Selection Based on Dot Pattern Mining

Fast web service selection approach is crucial for seamless and dynamic integration of e-business applications. However, since existing service selection approaches take up a lot of time, this make service selection out of time control. In this paper, we propose a fast web service selection (FWSS) approach for service composition system in e-business. In FWSS, only those services that fit to the context of users are valid candidates for the composition, and then mixed integer programming is used to find the most suitable service from above services. Experimental results show that our approach can fast perform service selection for web service composition.

The service composition makes use of the existing services to produce a new value added service to execute the complex business process. The service discovery finds the suitable services (candidates) for the various tasks of the composition based on the functionality. The service selection in composition assigns the best candidate for each tasks of the pre-structured composition plan based on the non-functional properties. In this paper, we propose the broker based architecture for the QoS and business offer aware Web service compositions. The broker architecture facilitates the registration of a new composite service into three different registries. The broker publishes service information into the service registry and QoS into the QoS registry. The business offers of the composite Web service are published into a separate repository called business offer (BO) registry. The broker employs the mechanism for the optimal assignment of the Web services to the individual tasks of the composition. The assignment is based on the composite service providers’s (CSP) variety of requirements defined on the QoS and business offers. The broker also computes the QoS of resulting composition and provides the useful information for the CSP to publish thier business offers.

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.

Service-oriented architecture permits the composition of web services provided with different Quality of Service (QoS) levels. In a given composition, finding the set of services that optimises some QoS attributes under its constraints is a problem that needs to be solved. Our aim is to propose an intelligent approach to the selection of a Composite Web Service (CWS) based on QoS. This paper reports the authors’ recent research on addressing the issue. An overview on the previously proposed approaches is presented. These approaches correspond to several improvements of an existing multi-agent one, which is well-cited in the specialised literature. Each framework, implemented on JADE (Java Agent Development) framework, improves another one in terms of CPU time and/or QoS score, to reach a new agent-based and scalable framework. The last framework utilises the agents’ ability of negotiation, interaction and cooperation in order to facilitate the selection of composite web services. By using CBR method, the agents can memorise QoS scores and availability. The improvements are related not only to the CPU time but also to the Composite QoS (CQoS) value, while operating in a dynamic environment and taking into account user preferences.

Web service selection, as an important part of web service composition, has direct influence on the quality of composite service. Many works have been carried out to find the efficient algorithms for quality of service (QoS)-aware service selection problem in recent years. In this paper, a negative selection immune algorithm (NSA) is proposed, and as far as we know, this is the first time that NSA is introduced into web service selection problem. Domain terms and operations of NSA are firstly redefined in this paper aiming at QoS-aware service selection problem. NSA is then constructed to demonstrate how to use negative selection principle to solve this question. Thirdly, an inconsistent analysis between local exploitation and global planning is presented, through which a local alteration of a composite service scheme can transfer to the global exploration correctly. It is a general adjusting method and independent to algorithms. Finally, extensive experimental results illustrate that NSA, especially for NSA with consistency weights adjusting strategy (NSA+), significantly outperforms particle swarm optimization and clonal selection algorithm for QoS-aware service selection problem. The superiority of NSA+ over others is more and more evident with the increase of component tasks and related candidate services.

The web service has widely spread in recent years which is showed by the large number of published web services. However, users may not always find their needs in one web service which has consequently spawned a composition of web services. This composition lead to many task difficulties including the selection of web services, which also consists of choosing the best QoS-based services among other similar services provided. From this perspective, there are several approaches to the selection of web services, however, this remains deficient at the level of execution time due to the rage number of competing web services. In this paper, we propose a new selection approach based on prefiltering and Skyline, this approach is tested and improved using a real dataset. We used two steps to solve this problem, prefiltering and Skyline. The first step is the use of K-Means clustering to bundle web services with similar Quality of Service (QoS) properties under one umbrella is explored. The second one is defining the most dominant web service using the Branch-and-Bound Skyline algorithm.

In an uncertain and changing environment, a composite service needs to continuously optimize its business process and service selection through runtime adaptation. To achieve the overall satisfaction of stakeholder requirements, quality tradeoffs are needed to adapt the composite service in response to the changing environments. Existing approaches on service selection and composition, however, are mostly based on quality preferences and business processes decisions made statically at the design time. In this paper, we propose a requirements-driven self-optimization approach for composite services. It measures the quality of services (QoS), estimates the earned business value, and tunes the preference ranks through a feedback loop. The detection of unexpected earned business value triggers the proposed self-optimization process systematically. At the process level, a preference-based reasoner configures a requirements goal model according to the tuned preference ranks of QoS requirements, reconfiguring the business process according to its mappings from the goal configurations. At the service level, selection decisions are optimized by utilizing the tuned weights of QoS criteria. We used an experimental study to evaluate the proposed approach. Results indicate that the new approach outperforms both fixed-weighted and floating-weighted service selection approaches with respect to earned business value and adaptation flexibility.

With trust degree set to be the foundation of component service selection in composite service, the execution and selection of composite services could be carried out more effectively based on the trust degree of service; It is favorable for those component services with higher trust degree to join into the process of service composition, thus, enhances the trustiness of composite service. Through introducing trust concept into service composition, trust-enhanced component service selection problem is discussed. Mathematical model of component service selection is established, and then selection algorithm based on the ant colony system is designed. Experiment results prove that the algorithms for trust-enhanced component service selection have a good optimizing performance.

Web service composition is a promising solution for building distributed applications on the e-business processes, and with web services providing similar functional characteristics, Quality of Service (QoS) is the main factor to differentiate them. It is imperative to provide service consumers with facilities for selecting the only web services for their requirement according to their non-functional characteristics or QoS. However, the selection process is too greatly complicated to meet the requirement of business process. In this paper, the key business process performance model (KBPP) is proposed, and further, the issue of QoS driven service selection for dynamic web service composition is investigated. From the point of view of requirement of KBPP, an evaluation framework with KBPP is proposed, and a new approach to optimize the service selecting based on KBPP is presented. Experimental results show that the proposed approach greatly improves the service selection process in a dynamic and uncertain environment of web services. Simulative experiments are conducted to show the validity and efficiency of the methods.

Web Services are materialized as a major technology carried out for automated interaction between distributed and miscellaneous applications. It is defined as a software service that provides business solutions consumed by different service requester. It can be accessed by a standard web protocol. Service composition is the mechanism used for selecting, reusing and combining existing web services to build new web services. With immense increase in web services, quality assessment plays an essential role in the selection approach. QoS is defined as the ability to guarantee the requirements like latency, reliability, bandwidth, etc. in order to satisfy a service level agreement between an application provider and end-user. QoS based dynamic service composition leads to the upward growth of an organization that implements multiple services to provide its business solution. The proposed research work elaborates the research work on different methodologies of QoS prediction with its implications to provide a proper road map for future research on efficient service composition.

Composing several API-defined services into one composite service per user requirements has become an important service creation approach in the cloud-enabled API economy. Various service selection approaches in support of service composition on demand have been proposed. They usually assume that networking resources are over-provisioned and their usage needs not be considered when making quality-aware service composition decisions. In practice, these approaches often lead to wasteful network resource consumption and impractical end-to-end QoS optimality for cloud-based services. This paper proposes a network-aware cloud service composition approach, named NetMIP, with comparative experimental evaluations for the clouds that adopt the widely deployed fat-tree network topology. By formalizing the service composition goal as a multi-objective constraint optimization problem, we have validated the proposed approach can be used to effectively reduce network resource consumption and deliver QoS optimality while satisfying the end-to-end QoS constraints for the candidate composite services in the cloud. The comparative experimental evaluations are done via a credible cloud infrastructure simulation system, named WebCloudSim. Extensive evaluation results show that NetMIP outperforms several representative cloud service composition approaches in terms of network resource consumption, QoS optimality, and computation time under various service selection workloads and fat-tree network topology settings.

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.

Managing Service Level Agreement (SLA) for composite semantic web services is a very complex process, as it involves many complex tasks such as components discovery, provisioning, monitoring, recovery, and coordination. Indeed, managing all these tasks manually is a very cumbersome operation, nevertheless it is time consuming and prone to errors. To overcome such problems, automated SLA management for composite semantic web services is needed. This requires the SLA of the composite service to be described in a machine-understandable format such that it can be understood and processed by the automated SLA management tool. Currently, there is no SLA description language for composite semantic web services, but there exists an SLA description language for atomic web services, known as the Web Service Level Agreement (WSLA). Hence, in this paper, we aim to extend the WSLA language to describe composite semantic web services' SLAs, then we show how we can automatically generate the components' SLAs from the composite semantic web services' SLAs; adopting the CRECENT framework that we previously proposed for managing composite web services.

We propose an efficient method to detect conflicts, which may occur during the execution time of composite web services, based on model checking. The proposed method does not only check whether a composite service satisfies the correctness claims specified by a service developer, but it also detects any possible conflicts from the control and data flow of a composite service at the time of service development. The proposed method divides correctness claims into four types depending on their application time: pre/post-condition, policy, and assumption. Specifically, composite services and correctness claims are modelled by OWL-S and SWRL, respectively. The proposed method automatically converts the control and data flow of an OWLS composite service and the correctness claims into Promela code and LTL formulas, which are given as the input of a SPIN model checker. Experimental results under real-world scenarios show that the proposed method detects conflicts in composite web services effectively.

Online services encapsulate enterprises, people, software systems and often operate in poorly understood environments. Using such services in tandem to predictably orchestrate a complex task is one of the principal challenges of service-oriented computing. A composite service orchestration soliciting multiple atomic services is plagued by a number of sources of variation. For instance, availability of an atomic service and its response time are two important sources of variation. Moreover, the number of possible variations in a composite service increases exponentially with increase in the number of atomic services. Testing such a composite service presents a crucial challenge as its often very expensive to exhaustively examine the variation space. Can we effectively test the dynamic behavior of a composite service using only a subset of these variations? This is the question that intrigues us. In this paper, we first model composite service variability as a feature diagram (FD) that captures all valid configurations of its orchestration. Second, we apply pairwise testing to sample the set of all possible configurations to obtain a concise subset. Finally, we test the composite service for selected pairwise configurations for a variety of QoS metrics such as response time, data quality, and availability. Using two case studies, Car crash crisis management and eHealth management, we demonstrate that pairwise generation effectively samples the full range of QoS variations in a dynamic orchestration. The pairwise sampling technique eliminates over 99% redundancy in configurations, while still calling all atomic services at least once. We rigorously evaluate pairwise testing for the criteria such as: a) ability to sample the extreme QoS metrics of the service b) stable behavior of the extracted configurations c) compact set of configurations that can help evaluate QoS tradeoffs and d) comparison with random sampling.