QoS-aware component composition

Component’s QoS constraints cannot be ignored when composing them to build reliable loosely-coupled, distributed systems. Therefore they should be explicitly taken into account in any formal model for component-based development. Such is the purpose of this paper: to extend a calculus of component composition to deal, in an effective way, with QoS constraints. Particular emphasis is put on how the laws that govern composition can be derived, in a calculational, pointfree style, in this new model

A calculus for generic, QoS-aware component composition

Software QoS properties, such as response time, availability, bandwidth requirement, memory usage, among many others, play a major role in the processes of selecting and composing software components. This paper extends a component calculus to deal, in an effective way, with them. The calculus models components as generalised Mealy machines, i.e., state-based entities interacting along their life time through well defined interfaces of observers and actions. QoS is introduced through an algebraic structure specifying the relevant QoS domain and how its values are composed under different disciplines. A major effect of introducing QoS-awareness is that a number of equivalences holding in the plain calculus become refinement laws. The paper also introduces a prototyper for the calculus developed as a ‘proof-of-concept’ implementation.FCT -Fuel Cell Technologies Program(FCOMP-01-0124-FEDER-020537

Service Selection of Ensuring Transactional Reliability and QoS for Web Service Composition

Service-Oriented Architecture (SOA) provides a flexible framework of service composition. Using standard-based protocols, composite service can be constructed by integrating component services independently. As component services are developed by different organization and offer diverse transactional properties and QoS characteristics, it is a challenging problem how to select suitable component services which ensure reliable execution of composite Web service and construct the optimal composite Web service. In this paper, we propose a selection approach that combines transactional properties of ensuring reliability and QoS characteristics. In the selection approach, we build automaton model to implement transactional-aware service selection and use the model to guarantee reliable execution of composite Web service. We also define aggregation functions, and use a Multiple-Attribute Decision-Making approach for the utility function to achieve Qos-based optimal service selection. Finally, two scenarios of experiments are presented to demonstrate the validity of the selection approach

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

Model Based Development of Quality-Aware Software Services

Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration

Design, implementation and evaluation of a QoS-aware transport protocol

In the context of a reconfigurable transport protocol framework, we propose a QoS-aware Transport Protocol (QSTP), specifically designed to operate over QoS-enabled networks with bandwidth guarantee. QSTP combines QoS-aware TFRC congestion control mechanism, which takes into account the network-level bandwidth reservations, with a Selective ACKnowledgment (SACK) mechanism in order to provide a QoS-aware transport service that fill the gap between QoS enabled network services and QoS constraint applications. We have developed a prototype of this protocol in the user-space and conducted a large range of measurements to evaluate this proposal under various network conditions. Our results show that QSTP allows applications to reach their negotiated QoS over bandwidth guaranteed networks, such as DiffServ/AF network, where TCP fails. This protocol appears to be the first reliable protocol especially designed for QoS network architectures with bandwidth guarantee