The emerging Service-Oriented Computing (SOC) paradigm promises to enable businesses and organizations to collaborate in an unprecedented way by means of standard web services. To support rapid and dynamic composition of services in this paradigm, web services that meet requesters' functional requirements must be able to be located and bounded dynamically from a large and constantly changing number of service providers based on their Quality of Service (QoS). In order to enable quality-driven web service selection, we need an open, fair, dynamic and secure framework to evaluate the QoS of a vast number of web services. The fair computation and enforcing of QoS of web services should have minimal overhead but yet able to achieve su#cient trust by both service requesters and providers. In this paper, we presented our open, fair and dynamic QoS computation model for web services selection through implementation of and experimentation with a QoS registry in a hypothetical phone service provisioning market place application.

Emerging Web services standards enable the development of large-scale applications in open environments. In particular, they enable services to be dynamically bound. However, current techniques fail to address the critical problem of selecting the right service instances. Service selection should be determined based on user preferences and business policies, and consider the trustworthiness of service instances. We propose a multiagent approach that naturally provides a solution to the selection problem. This approach is based on an architecture and programming model in which agents represent applications and services. The agents support considerations of semantics and quality of service (QoS). They interact and share information, in essence creating an ecosystem of collaborative service providers and consumers. Consequently, our approach enables applications to be dynamically configured at runtime in a manner that continually adapts to the preferences of the participants. Our agents are designed using decision theory and use ontologies. We evaluate our approach through simulation experiments.

Recently, Web services gain momentum for developing flexible service-oriented architectures. Quality of service (QoS) issues are currently not part of the Web service standard stack, although non-functional attributes like performance, dependability or cost and payment play an important role for service discovery, selection, and composition. A lot of research is dedicated to different QoS models, at the same time omitting a way to specify how QoS parameters (esp. the performance related aspects) are assessed, evaluated and constantly monitored. Our contribution in this paper comprises a) an evaluation approach for QoS attributes of Web services, which works completely serviceand provider independent, b) a method to analyze Web service interactions by using our evaluation tool and extract important QoS information without any knowledge about the service implementation. Furthermore, our implementation allows assessing performance specific values (such as latency or service processing time) that usually require access to the server which hosts the service. The result of the evaluation process can be used to enrich existing Web service descriptions with a set of up-to-date QoS attributes, therefore, making it a valuable instrument for Web service selection. 1.

The rapid growth of time-critical information services and business-oriented applications is making quality of service (QoS) support increasingly important in content distribution. This paper investigates the problem of placing object replicas (e.g., web pages and images) to meet the QoS requirements of clients with the objective of minimizing the replication cost. We consider two classes of service models: replica-aware service and replica-blind service. In the replica-aware model, the servers are aware of the locations of replicas and can therefore direct requests to the nearest replica. We show that the QoS-aware placement problem for replica-aware services is NP-complete. Several heuristic algorithms for efficient computation of suboptimal solutions are proposed and experimentally evaluated. In the replica-blind model, the servers are not aware of the locations of replicas or even their existence. As a result, each replica only serves the requests flowing through it under some given routing strategy. We show that there exist polynomial optimal solutions to the QoS-aware placement problem for replicablind services. Efficient algorithms are proposed to compute the optimal locations of replicas under different cost models.

Contributions in the field of Web services have identified that (a) finding matches between semantic descriptions of advertised and requested services and (b) non-functional characteristics – the Quality of Service (QoS) – are the most crucial criteria for composition of Web services. In this work a mechanism is introduced that determines the QoS of a Web service composition by aggregating the QoS dimensions of the individual services. This allows to verify whether a set of services selected for composition satisfies the QoS requirements for the whole composition. The aggregation performed builds upon abstract composition patterns, which represent basic structural elements of a composition, like sequence, loop, or parallel execution. This work focusses on workflow management environments. This paper defines composition patterns that are derived from Van der Aalst’s et al. comprehensive collection of Workflow Patterns. The resulting aggregation schema supports the same structural elements as found in workflows. Furthermore, the aggregation of serveral QoS dimensions is discussed. 1

Abstract. Automating Service Oriented Architectures by augmenting them with semantics will form the basis of the next generation of computing. Selection of service still is an important challenge, especially, when a set of services fulfilling user’s capabilities requirements have been discovered, among these services which one will be eventually invoked by user is very critical, generally depending on a combined evaluation of qualities of services (Qos). This paper proposes a QoS-based selection of services. Initially we specify a QoS ontology and its vocabulary using the Web Services Modeling Ontology (WSMO) for annotating service descriptions with QoS data. We continue by defining quality attributes and their respective measurements along with a QoS selection model. Finally, we present a fair and dynamic selection mechanism, using an optimum normalization algorithm. 1

QoS-aware dynamic binding of composite services provides the capability of binding each service invocation in a composition to a service chosen among a set of functionally equivalent ones to achieve a QoS goal, for example minimizing the response time while limiting the price under a maximum value. This paper proposes a QoS-aware binding approach based on Genetic Algorithms. The approach includes a feature for early run-time re-binding whenever the actual QoS deviates from initial estimates, or when a service is not available. The approach has been implemented in a framework and empirically assessed through two different service compositions.

Abstract—The rapid growth of new information services and business-oriented applications entails the consideration of quality of service (QoS) in content distribution. This paper investigates the QoS-aware replica placement problems for responsiveness QoS requirements. We consider two classes of service models: replica-aware services and replica-blind services. In replica-aware services, the servers are aware of the locations of replicas and can therefore optimize request routing to improve responsiveness. We show that the QoS-aware placement problem for replica-aware services is NP-complete. Several heuristic algorithms for fast computation of good solutions are proposed and experimentally evaluated. In replica-blind services, the servers are not aware of the locations of replicas or even their existence. As a result, each replica only serves the requests flowing through it under some given routing strategy. We show that there exist polynomial optimal solutions to the QoS-aware placement problem for replica-blind services. Efficient algorithms are proposed to compute the optimal locations of replicas under different cost models. Index Terms—Content distribution, replication, placement, quality of service, dynamic programming, NP-complete. 1

Abstract—Service level agreements (SLAs), or contracts, have an important role in Web services. These contracts define the obligations and rights between the provider of a Web service and its client, with respect to the function and the Quality of Service (QoS). For composite services like orchestrations, such contracts are deduced by a process called QoS contract composition, based on contracts established between the orchestration and the called Web services. These contracts are typically stated in the form of hard guarantees (e.g., response time always less than 5 msec). Using hard bounds is not realistic, however, and more statistical approaches are needed. In this paper, we propose using soft probabilistic contracts instead, which consist of a probability distribution for the considered QoS parameter—in this paper, we focus on timing. We show how to compose such contracts to yield a global probabilistic contract for the orchestration. Our approach is implemented by the TOrQuE tool. Experiments on TOrQuE show that overly pessimistic contracts can be avoided and significant room for safe overbooking exists. An essential component of SLA management is then the continuous monitoring of the performance of called Web services to check for violations of the agreed SLA. We propose a statistical technique for runtime monitoring of soft contracts.

Recently, Web Services (WSs) have evolved to a quite popular research field. Nevertheless, there are obstacles that prevent the introduction of WS provision in the wide market. Among these is the inability to represent the non-functional features of WSs, i.e. their Quality-of-Service. Integrating QoS features in WS profiles is to the advantage of both users and providers, as it enables QoS-aware WS selection and composition addressing the user’s QoS requirements and objectives, while giving WS providers a significant competitive advantage in the e-business domain, also maximizing their resources ’ utilization. This paper focuses on the formulation of a QoS ontology framework that is used to support QoS-aware WS provision. It is based on work carried out in the IST-Amigo 1 Integrated Project for Ambient Intelligence (AmI) homes, which, exploiting heterogeneous technologies and infrastructures, aims to develop an open, standardized, interoperable middleware for the provision of QoS-aware AmI WSs to domestic users. 1.