Quality of service support for service discovery and selection in service oriented computing environment

Service oriented computing (SOC) represents a new generation of web architecture. Central to SOC is the notion of services, which are self-contained, self-describing, modular applications that can be published, located, and invoked across the Internet. The services represent capability, which can be anything from simple operations to complicated business processes. This new architecture offers great potential for e-commerce applications, where software agents can automatically find and select the services that best serve a consumer's interests. Many techniques have been proposed for discovery and selection of services, most of which have been constructed without a formal Quality of Service (QoS) model or much regard to understanding the needs of consumers. This thesis aims to provide QoS support for the entire SOC life cycle, namely: (i) extend current approaches to service discovery that allow service providers to advertise their services in a format that supports quality specifications, and allows service consumers to request services by stating required quality levels, (ii) support matchmaking between advertised and requested services based on functional as well as quality requirements, (iii) perform QoS assessment to support consumers in service selection. Many techniques exists for performing QoS assessment, most of which are based on collecting quality ratings from the users of a service. This thesis argues that collecting quality ratings alone from the users is not sufficient for deriving a reliable and accurate quality measure for a service. This is because different users often have different expectations and judgements on the quality of a service and their ratings tend to be closely related to these expectations, i.e., how their expectations are met. The thesis proposes a new model for QoS assessment, based on user expectations that collects expectations as well as ratings from the users of a service, then calculates the QoS using only the ratings which were judged on similar expectations.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Quality of service support for service discovery and selection in service oriented computing environment

Service oriented computing (SOC) represents a new generation of web architecture. Central to SOC is the notion of services, which are self-contained, self-describing, modular applications that can be published, located, and invoked across the Internet. The services represent capability, which can be anything from simple operations to complicated business processes. This new architecture offers great potential for e-commerce applications, where software agents can automatically find and select the services that best serve a consumer's interests. Many techniques have been proposed for discovery and selection of services, most of which have been constructed without a formal Quality of Service (QoS) model or much regard to understanding the needs of consumers. This thesis aims to provide QoS support for the entire SOC life cycle, namely: (i) extend current approaches to service discovery that allow service providers to advertise their services in a format that supports quality specifications, and allows service consumers to request services by stating required quality levels, (ii) support matchmaking between advertised and requested services based on functional as well as quality requirements, (iii) perform QoS assessment to support consumers in service selection. Many techniques exists for performing QoS assessment, most of which are based on collecting quality ratings from the users of a service. This thesis argues that collecting quality ratings alone from the users is not sufficient for deriving a reliable and accurate quality measure for a service. This is because different users often have different expectations and judgements on the quality of a service and their ratings tend to be closely related to these expectations, i.e., how their expectations are met. The thesis proposes a new model for QoS assessment, based on user expectations that collects expectations as well as ratings from the users of a service, then calculates the QoS using only the ratings which were judged on similar expectations

Consulting (in Writing) to the Corporation: Principles and Pragmatics

Provenance information provides a useful basis to verify whether a particular application behavior has been adhered to. This is particularly useful to evaluate the basis for a particular outcome, as a result of a process, and to verify if the process involved in making the decision conforms to some pre-defined set of rules. This is significant in a healthcare scenario, where it is necessary to demonstrate that patient data has been processed in a particular way. Understanding how provenance information may be recorded, stored, and subsequently analyzed by a decision maker is therefore significant in a service oriented architecture, which involves the use of third party services over which the decision maker does not have control. The aggregation of data from multiple sources of patient information plays an important part in subsequent treatments that are proposed for a patient. A tool to navigate through and analyze such provenance information is proposed, based on the use of a portal framework that allows different views on provenance information to co-exist. The portal enables users to add custom portlets enabling application specific views that would facilitate particular decision making

Trust Assessment Using Provenance in Service Oriented Applications

Workflow forms a key part of many existing Service Oriented applications, involving the integration of services that may be made available at distributed sites. It is possible to distinguish between an "abstract" workflow description outlining which services must be involved in a workflow execution and a "physical" workflow description outlining the particular instances of services that were used in a particular enactment. Provenance information provides a useful way to capture the physical workflow description automatically especially if this information is captured in a standard format. Subsequent analysis on this provenance information may be used to evaluate whether the abstract workflow description has been adhered to, and to enable a user executing a workflow-based application to establish "trust" in the outcome

Expectation-based quality of service assessment

The ability to gauge quality of service is critical if we are to realise the potential of the service-oriented computing paradigm. Many techniques have been proposed for calculating the quality of a service, and they do so typically by collecting quality ratings from the users of the service, then combining them in one way or another to derive the quality of the service. We argue that collecting quality ratings alone from the users is not sufficient for deriving a reliable and accurate quality measure for a service. This is because different users often have different expectations on the quality of a service and their ratings tend to be closely related to these expectations, i.e. how their expectations are met. In this paper, we propose a quality of service assessment model based on user expectations. That is, we collect expectations as well as ratings from the users of a service, then calculate the quality of the service using only the ratings that have similar expectations. Our experiments show that the method we propose here can result in more meaningful and reliable quality ratings for services

Modelling quality of service in service oriented computing

The ability to gauge quality of service is critical if we are to realise the potential of the service-oriented computing paradigm. Many techniques have been proposed for calculating the quality of a service, and they do so typically by collecting quality ratings from the users of the service, then combining them in one way or another to derive the quality of the service. We argue that combining quality ratings in such a way may lead to inaccurate quality measures for services. This is because different users often have different expectations on the quality of a service and their ratings tend to be closely related to these expectations, i.e. how their expectations are met. In this paper, we propose a fuzzy based quality of service assessment model based on user expectations. That is, we collect expectations as well as ratings from the users of a service, then calculate the quality of the service based on the ratings that have similar expectations. We give examples to show that our approach can result in a more accurate and meaningful measure for quality of service

Supporting QoS based selection in service oriented architecture

The ability to gauge quality of service is critical if we are to realise the potential of the service-oriented computing paradigm. Many techniques have been proposed for calculating the quality of a service, and they do so typically by collecting quality ratings from the users of the service, then combining them in one way or another to derive the quality of the service. We argue that combining quality ratings in such a way may lead to inaccurate quality measures for services. This is because different users often have different expectations on the quality of a service and their ratings tend to be closely related to these expectations, i.e. how their expectations are met. In this paper, we propose a quality of service assessment model that is able to capture the reason behind the ratings. This allows us to perform quality of service assessment in context, by using only the ratings that have similar expectations. We also introduce a confidence score that adjusts a rating of harsh or lenient rater. This is established by analyzing a user's past rating behavior for services. Our experiments show that the method we propose here can result in more meaningful and reliable selection of services

Establishing Workflow Trust Using Provenance Information

Abstract. Workflow forms a key part of many existing Service Oriented applications, involving the integration of services that may be made available at distributed sites. It is possible to distinguish between an “abstract” workflow description outlining which services must be involved in a workflow execution and a “physical ” workflow description outlining the instances of services that were used in a particular enactment. Provenance information provides a useful way to capture the physical workflow description automatically- especially if this information is captured in a standard format. Subsequent analysis on this provenance information may be used to evaluate whether the abstract workflow description has been adhered to, and to enable a user executing a workflow-based application to establish “trust ” in the outcome. An analysis tool that makes use of provenance information to assist in evaluating trust in the outcome of a workflow execution is presented. The analysis tool makes use of a rule-based engine, supporting a range of queries on the recorded information by one or more workflow enactors. The results of the analysis tool on a particular workflow scenario are presented, along with an experiment demonstrating how the analysis tool would scale as the granularity of the recorded provenance information was increased.