A survey of QoS-aware web service composition techniques

Web service composition can be briefly described as the process of aggregating services with disparate functionalities into a new composite service in order to meet increasingly complex needs of users. Service composition process has been accurate on dealing with services having disparate functionalities, however, over the years the number of web services in particular that exhibit similar functionalities and varying Quality of Service (QoS) has significantly increased. As such, the problem becomes how to select appropriate web services such that the QoS of the resulting composite service is maximized or, in some cases, minimized. This constitutes an NP-hard problem as it is complicated and difficult to solve. In this paper, a discussion of concepts of web service composition and a holistic review of current service composition techniques proposed in literature is presented. Our review spans several publications in the field that can serve as a road map for future research

QoS-Aware Middleware for Web Services Composition

The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online Business-to-Business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different Quality of Service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

A Framework for Quality-Driven Delivery in Distributed Multimedia Systems

In this paper, we propose a framework for Quality-Driven Delivery (QDD) in distributed multimedia environments. Quality-driven delivery refers to the capacity of a system to deliver documents, or more generally objects, while considering the users expectations in terms of non-functional requirements. For this QDD framework, we propose a model-driven approach where we focus on QoS information modeling and transformation. QoS information models and meta-models are used during different QoS activities for mapping requirements to system constraints, for exchanging QoS information, for checking compatibility between QoS information and more generally for making QoS decisions. We also investigate which model transformation operators have to be implemented in order to support some QoS activities such as QoS mapping

Investigating Decision Support Techniques for Automating Cloud Service Selection

The compass of Cloud infrastructure services advances steadily leaving users in the agony of choice. To be able to select the best mix of service offering from an abundance of possibilities, users must consider complex dependencies and heterogeneous sets of criteria. Therefore, we present a PhD thesis proposal on investigating an intelligent decision support system for selecting Cloud based infrastructure services (e.g. storage, network, CPU).Comment: Accepted by IEEE Cloudcom 2012 - PhD consortium trac