Quality Of Service Preferences Research Articles

Towards optimal discovery of web services for multiple QoS constraints and preferences

Web service discovery (WSD) is the task of matchmaking a set of relevant web services. Quality of service (QoS) has recently been applied to represent non-functional properties of web services. Therefore, when those services provide the same functionality but have different QoS values, how to effectively filter out the services that cannot satisfy the QoS constraints and rank the remaining services is still an open research issue. In this paper, we propose an integrated approach that allows a service requester to specify a functionality request, multiple QoS constraints and their preferences, and our method discovers a set of the most appropriate ranked services with QoS utility aggregation. By conducting empirical experiments on simulated web services, we validate the feasibility of our service discovery approach. The running example shows that, our approach can find more appropriate services by the satisfiability of multiple QoS constraints and the ranking of aggregated QoS.

A QoS preference-based algorithm for service composition in service-oriented network

Quality of service (QoS) based provisioning for service-oriented network applications has been actively discussed because of user's specific requirements. An order relation vector model is proposed in this paper, which can be used to represent and calculate user's preference information effectively. User's preference order of QoS attributes is a possible approach to formulate user's specific QoS requirements in the context. In order to apply the preference order to actual application, a QoS attribute matrix is introduced to manage QoS attribute value; at the same time, a feasible method of defuzzifying and normalizing is also introduced to deal with the original QoS attribute matrix; user's preference order and the normalized QoS attribute matrix are used to calculate user's QoS attribute weight vector, which can be regarded as an evaluation criterion reflecting user's different QoS preference degrees. Finally, a service composition model and algorithm is proposed in this paper. The numerical examples indicate that the model delivers user's QoS preference reliably and the experiment shows that the algorithm is efficient.

Modeling of Bus Transit Driver Availability for Effective Emergency Evacuation in Disaster Relief

Potential evacuees without access to personal automobiles are expected to use transit, especially buses, to reach safer regions. For a transit agency, operation problems to be considered include establishing bus launch areas, positioning the minimum number of required buses, and coordinating transit operators, especially determining whether the number of drivers will be sufficient to cover the number of vehicles (i.e., buses) to be used during the evacuation. It is also highly probable that during an emergency, absenteeism rates for bus drivers might increase. In this study, the authors developed two stochastic models to determine the need for extra drivers during an emergency evacuation and to provide optimal solutions using well-established concepts in mathematical programming. First, the authors reviewed the literature to develop an effective methodology for the development of optimal extraboard management strategies. The authors found that although several recent reports clearly mentioned the problem of not having enough bus drivers during emergency evacuation operations, no analytical study incorporated the optimal extraboard size problem into emergency evacuation operations. Second, two mathematical models are presented in this paper. The aim of the developed models is to fill the gap in the literature for determining optimal extraboard size for transit operations during emergency evacuations. The models are specifically designed to capture risk-averse behavior of decision makers. Finally, these models were tested with hypothetical examples from real-world data from New Jersey. Results show that both models give reasonable extraboard size estimates, and under different conditions, these models are responsive to the changes in cost and quality of service preferences. The results are encouraging in terms of the models' usefulness for real-world applications.

Intégration de préférences dans la découverte et la sélection des services web

Les methodes actuelles pour la decouverte de services basees sur le comportement – decrit comme un processus metier (PM) – retournent encore un grand nombre de services offrant des fonctionnalites similaires. Dans cet article, nous proposons une strategie d’evaluation pour la recherche de services basee sur les quantificateurs linguistiques flous et qui prend en compte la similarite structurelle entre les PM de services et la satisfaction des preferences sur les attributs de qualite de services (QdS). La requete utilisateur et les PM cibles sont representes a l’aide de graphes annotes ; les preferences de QdS sont modelisees au moyen des ensembles flous.

Web Service Selection Based on Ranking of QOS Using Associative Classification

With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user's preferences. The similarity measure (outputs-inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services. In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user's QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters' non-functional requirements.

A decomposition-based approach for service composition with global QoS guarantees

Service-oriented architecture has offered an opportunity to quickly and independently develop new business applications from the existing services. Given that many services are available with the same function but different quality of service (QoS) properties, and service users have different QoS preferences, the challenge of service composition is to select appropriate service candidates to maximize the overall utility while satisfying a user’s requirements. In this paper, we propose a decomposition-based approach for service composition, in which the utility of a composite service can be computed from the utilities of component services and the constraints of component services can be derived from the constraints of the composite service. Thus, with our approach, it is possible to independently manage the selection of each component service, leading to more scalability and more flexibility for service composition in a dynamic environment. The experiment studies show that our approach can achieve a near-optimal solution with a significantly improved performance in computation time.

WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATION

With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services. In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.

Network Economies for the Internet-Application Models

We propose a decentralized model of network and server economies, where we show efficient QoS (Quality of Service) provisioning and Pareto allocation of resources (network and server resources) among agents and suppliers, which are either network routers or servers (content providers). Specifically, it is shown 1) how prices for resources are set at the suppliers based on the QoS demands from the agents and 2) how dynamic routing algorithms and admission control mechanisms based on QoS preferences emerge from the user classes for the network economy.

The Representation and Computation of QoS Preference with Its Applications in Grid Computing Environments

In Grid computing environment, quality of service (QoS) provisioning must be provided to the end users on the basis of their specific requirements. This paper proposes in a first step QoS attributes for Grid applications. In this matter, a mix of quantitative and qualitative parameters have to be considered. In the context, the analytical hierarchy process (AHP) technique [1] is a possible approach to formulate the QoS requirements of the users for Grid services. In order to apply QoS preference to actual application, we introduce a QoS function and a metric for user's satisfaction degrees. These both tools can be used as an evaluation criterion by the user. Subsequently, an algorithm of service selection considering the user's QoS preference is presented. Our empirical studies indicate that the application can reliably select the optimal service for users.

Dynamic selection mechanism for quality of service aware web services

A web service is an interface of the software component that can be accessed by standard Internet protocols. The web service technology enables an application to application communication and interoperability. The increasing number of web service providers throughout the globe have produced numerous web services providing the same or similar functionality. This necessitates the use of tools and techniques to search the suitable services available over the Web. UDDI (universal description, discovery and integration) is the first initiative to find the suitable web services based on the requester's functional demands. However, the requester's requirements may also include non-functional aspects like quality of service (QoS). In this paper, the authors define a QoS model for QoS aware and business driven web service publishing and selection. The authors propose a QoS requirement format for the requesters, to specify their complex demands on QoS for the web service selection. The authors define a tree structure called quality constraint tree (QCT) to represent the requester's variety of requirements on QoS properties having varied preferences. The paper proposes a QoS broker based architecture for web service selection, which facilitates the requesters to specify their QoS requirements to select qualitatively optimal web service. A web service selection algorithm is presented, which ranks the functionally similar web services based on the degree of satisfaction of the requester's QoS requirements and preferences. The paper defines web service provider qualities to distinguish qualitatively competitive web services. The paper also presents the modelling and selection mechanism for the requester's alternative constraints defined on the QoS. The authors implement the QoS broker based system to prove the correctness of the proposed web service selection mechanism.

Treatment strategy and its application for QoS preference in network computing environment

To ensure users' requirements for service on demand,the paper went deep into the treatment strategy of Quality of Service(QoS) preference information.Three ways were first put forward to describe QoS preference information based on the theory of multiple-attribute decision,which were orders vector,AHP matrix and language valuation collection,and the concrete methods of conversion and computation were given out.Afterward,the treatment strategy of QoS preference was applied to service selection,and a decision method of the optimal service was presented,which could reflect users' QoS preference and meet users' requirements for service on demand.The specific example with analysis indicates that the treatment strategy of QoS preference in the paper is feasible.

An Ant Colony Optimization Approach to a Grid Workflow Scheduling Problem With Various QoS Requirements

Grid computing is increasingly considered as a promising next-generation computational platform that supports wide-area parallel and distributed computing. In grid environments, applications are always regarded as workflows. The problem of scheduling workflows in terms of certain quality of service (QoS) requirements is challenging and it significantly influences the performance of grids. By now, there have been some algorithms for grid workflow scheduling, but most of them can only tackle the problems with a single QoS parameter or with small-scale workflows. In this frame, this paper aims at proposing an ant colony optimization (ACO) algorithm to schedule large-scale workflows with various QoS parameters. This algorithm enables users to specify their QoS preferences as well as define the minimum QoS thresholds for a certain application. The objective of this algorithm is to find a solution that meets all QoS constraints and optimizes the user-preferred QoS parameter. Based on the characteristics of workflow scheduling, we design seven new heuristics for the ACO approach and propose an adaptive scheme that allows artificial ants to select heuristics based on pheromone values. Experiments are done in ten workflow applications with at most 120 tasks, and the results demonstrate the effectiveness of the proposed algorithm.

Efficient packet scheduling for heterogeneous multimedia provisioning over broadband satellite networks: An adaptive multidimensional QoS‐based design

AbstractWith their inherent broadcast capabilities and reliable extensive geographical coverage, the broadband satellite networks are emerging as a promising approach for the delivery of multimedia services in 3G and beyond systems. Given the limited capacity of the satellite component, to meet the diverse quality of service (QoS) demands of multimedia applications, it is highly desired that the available resources can be adaptively utilized in an optimized way. In this paper, we draw our attention on the development and evaluation of an efficient packet scheduling scheme in a representative broadband satellite system, namely satellite digital multimedia broadcasting (SDMB), which is positioned as one of the most attractive solutions in the convergence of a closer integration with the terrestrial mobile networks for a cost‐effective delivery of point‐to‐multipoint services. By taking into account essential aspects of a successful QoS provisioning while preserving the system power/resource constraints, the proposed adaptive multidimensional QoS‐based (AMQ) packet scheduling scheme in this paper aims to effectively satisfy diverse QoS requirements and adaptively optimize the resource utilization for the satellite multimedia broadcasting. The proposed scheme is formulated via an adaptive service prioritization algorithm and an adaptive resource allocation algorithm. By taking into account essential performance criteria, the former is capable of prioritizing contending flows based on the QoS preferences and performance dynamics, while the latter allocates the resources, in an adaptive manner, according to the current QoS satisfaction degree of each session. Simulation results show that the AMQ scheme achieves significantly better performance than those of existing schemes on multiple performance metrics, e.g. delay, throughput, channel utilization and fairness. Copyright © 2008 John Wiley & Sons, Ltd.

Improving brokering adaptation in dynamic heterogeneous environments

We here present an agent-based Quality of Service (QoS) negotiation framework that enables service providers to negotiate the level of QoS provided to end-users according to its own current state. In our model, end-users' QoS preferences are expressed in service requests along several dimensions. From this set of QoS constraints and information about end-users' devices our service configuration brokering facility is able to create and exploit different users' communities associated with their specific inferred stereotypes, in order to be helpful, in an adaptive way, in a dynamically changing environment populated with previously unknown entities (clients, users, machines, etc.).

Quality of service provision in noncooperative networks with diverse user requirements

This paper studies the quality of service (QoS) provision problem in noncooperative networks where applications or users are selfish and routers implement generalized processor sharing based packet scheduling. We formulate a model of QoS provision in noncooperative networks where users are given the freedom to choose both the service classes and traffic volume allocated, and heterogenous QoS preferences are captured by a user's utility function. We present a comprehensive analysis of the noncooperative multi-class QoS provision game, giving a complete characterization of Nash equilibria and their existence criteria, and show under what conditions they are Pareto- and system-optimal. We show that, in general, Nash equilibria need not exist, and when they do exist, they need not be Pareto- nor system-optimal. For certain “resource-plentiful” systems, however, we show that the world indeed can be nice with Nash equilibria, Pareto optima, and system optima collapsing into a single class. We study the problem of facilitating effective QoS in systems with multi-dimensional QoS vectors containing both mean- and burstiness-related QoS measures. We extend the game-theoretic analysis to multi-dimensional QoS vector games and show under what conditions the aforementioned results carry over.