Michael C. Jaeger

QoS aggregation for Web service composition using workflow patterns

Contributions in the field of Web services have identified that (a) finding matches between semantic descriptions of advertised and requested services and (b) nonfunctional characteristics - the quality of service (QoS) - are the most crucial criteria for composition of Web services. 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. We define composition patterns that are derived from Van der Aalsts et al. comprehensive collection of workflow patterns. The resulting aggregation schema supports the same structural elements as found in workflows. Furthermore, the aggregation of several QoS dimensions is discussed.

Ranked Matching for Service Descriptions Using OWL-S

Semantic Web services envision the automated discovery and selection of Web services. This can be realised by adding semantic information to advertised services and service requirements. The discovery and selection process finds matches between requirements and advertisements according to their semantic description. Based on the Web Ontology Language (OWL) an ontology for Web services (OWL-S) was introduced to standardise their semantic description. There are already some approaches available for matching of service requirements with service advertisements according to such an ontology.

QoS aggregation in Web service compositions

For the composition of Web services non-functional characteristics are commonly considered criteria for finding and selecting available services. Our work focuses on a mechanism that determines the overall quality-of-service (QoS) of a composition by aggregating the QoS of the individual services. With aggregated QoS it can be verified whether a set of services satisfies the QoS requirements for the whole composition or not. The aggregation performed builds upon abstract composition patterns, which model basic structural elements of a composition like parallel paths, a sequence, or a looped execution. In this work we extend existing composition patterns with the abilities to consider dependencies between services. Furthermore we introduce, how to use the pattern-based aggregation in the monitoring process during run-time. We explain how the data derived from the monitoring process can be used to calculate a more accurate aggregation of QoS for the composition.

QoS-Aware composition of web services: an evaluation of selection algorithms

A composition arranges available services resulting in a defined flow of executions. Before the composition is carried out, a discovery service identifies candidate services. Then, a selection process chooses the optimal candidates. This paper discusses how the selection can consider different Quality-of-Service (QoS) categories as selection criteria to select the most suitable candidates for the composition. If more than one category is used for optimisation, a multi-dimensional optimisation problem arises which results in an exponential computation effort for computing an optimal solution. We explain the problem and point out similarities to other combinatorial problems – the knapsack problem and the resource constraint project scheduling problem (RCPSP). Based on this discussion, we describe possible heuristics for these problems and evaluate their efficiency when used for web service candidate selection.

Monitoring Dependencies for SLAs: The MoDe4SLA Approach

In service oriented computing different techniques for monitoring service level agreements (SLAs) are available. Many of these monitoring approaches focus on bilateral agreements between partners. However, when monitoring composite services it is not only important to figure out whether SLAs are violated, but we also need to analyze why these violations have occurred. When offering a composite service a company depends on its content providers to meet the service level they agreed upon. Due to these dependencies a company should not only monitor the SLA of the composite service, but also the SLAs of the services it depends on. By analyzing and monitoring the composite service in this way, causes for SLA violations can be easier found. In this paper we demonstrate how to analyze SLAs during development phase and how to monitor these dependencies using event logs during runtime. We call our approach MoDe4SLA (monitoring dependencies for SLAs).

Transformations between UML and OWL-S

As the number of available Web services increases there is a growing demand to realize complex business processes by combining and reusing available Web services. The reuse and combination of services results in a composition of Web services that may also involve services provided in the Internet. With semantically described Web services, an automated matchmaking of capabilities can help identify suitable services. To address the need for semantically defined Web services, OWL-S and WSML have been proposed as competing semantic Web service languages. Both proposals are quite low-level and hard to use even for experienced Web service developers. We propose a UML profile for semantic Web services that enables the use of high-level graphical models as an integration platform for semantic Web services. The UML profile provides flexibility as it supports multiple semantic Web service languages. Transformations of both ways between OWL-S and UML are implemented to show that the UML profile is expressive enough to support one of the leading semantic Web service languages.

QoS-aware composition of Web services: a look at selection algorithms

When a composition of Web services is designed, available services are put together to form a defined flow of executions. In a discovery process, a trader proposes available Web services as potential candidates. In a succeeding selection, for each task a trader chooses one candidate to form the optimal composition due to selection criteria. This paper discusses how the selection can consider different quality-of-service (QoS) categories to determine the most suitable candidates for the composition. If more than one category is used for optimisation, a multi-dimensional optimisation problem arises. This mentions similarities to similar combinatorial problems. Then, possible solutions are proposed and their performance is evaluated.

Modeling QoS characteristics in WSMO

Service oriented architectures (SOAs) are becoming widespread solutions for realizing distributed applications. They promote a service view of the world in which functionalities exposed as services by different companies are assembled and reused in a standardized manner. Services are the core building blocks of SOAs and therefore modeling various aspects of services becomes a fundamental challenge. Among these aspects, quality-of-service (QoS) need to be addressed given the high dynamism of any SOA-based system. This paper introduces the basic steps of modeling QoS characteristics of services with the Web Service Modeling Ontology (WSMO) in order to provide a QoS-aware SOA. It discusses the current limitations of modeling QoS characteristics with WSMO and proposes a set of approaches towards a richer QoS modeling support. Each approach is analyzed in terms of complexity and the advantages and disadvantages of each approach are discussed.

A Cloud Environment for Data-intensive Storage Services

The emergence of cloud environments has made feasible the delivery of Internet-scale services by addressing a number of challenges such as live migration, fault tolerance and quality of service. However, current approaches do not tackle key issues related to cloud storage, which are of increasing importance given the enormous amount of data being produced in todays rich digital environment (e.g. by smart phones, social networks, sensors, user generated content). In this paper we present the architecture of a scalable and flexible cloud environment addressing the challenge of providing data-intensive storage cloud services through raising the abstraction level of storage, enabling data mobility across providers, allowing computational and content-centric access to storage and deploying new data-oriented mechanisms for QoS and security guarantees. We also demonstrate the added value and effectiveness of the proposed architecture through two real-life application scenarios from the healthcare and media domains.

Analyzing Impact Factors on Composite Services

Although Web services are intended for short term, ad hoc collaborations, in practice many Web service compositions are offered longterm to customers. While the Web services making up the composition may vary, the structure of the composition is rather fixed. For companies managing such Web service compositions, however, challenges arise which go far beyond simple bilateral contract monitoring. It is not only important to determine whether or not a component(i.e., Web service) in a composition is performing properly, but also to understand what the impact of its performance is on the overall service composition. In this paper we show which challenges emerge and we provide an approach on determining the impact each Web service has on the composition at runtime.