Service Oriented Computing Environment Research Articles

OPRC: An Online Personalized Reputation Calculation Model in Service-Oriented Computing Environments

Cloud applications based on service-oriented architectures usually integrate many component services to implement specific application logic. In service-oriented computing environments, many Web services are provided for users to build service-oriented systems. Since the performance of the same Web service varies according to different users' perspectives, the users have to personally select the optimal Web services according to the quality-of-service (QoS) data observed by other similar users. However, users with a low reputation provide unreliable data, which has a negative impact on service selection. Moreover, the QoS data vary over time due to changes in user reputation; and therefore, how to calculate a personalized reputation for each user at runtime remains a substantial problem. To address this critical challenge, this paper proposes an online reputation calculation method, called the OPRC, to efficiently provide a personalized reputation for each user. Based on the users' observed QoS data, the OPRC employs MF and online learning techniques to calculate personalized reputations. To validate the approach, large-scale experiments are conducted, which contain two QoS attributes from 142 reliable users and 15 unreliable users. The results show that OPRC has high accuracy and effectiveness compared to other approaches.

Effort Estimation for Service-Oriented Computing Environments

The concept of service in Service-Oriented Architecture (SOA) makes possible to introduce other ideas like service composition, governance and virtualization. Each of these ideas, when exercised to an enterprise level, provides benefits in terms of cost and performance. These ideas bring many new opportunities for the project managers in making the estimates of effort required to produce SOA systems. This is because the SOA systems are different from traditional software projects and there is a lack of efficient metrics and models for providing a high level of confidence in effort estimation. Thus, in this paper, an efficient estimation methodology has been presented based on analyzing the development phases of past SOA based software systems. The objective of this paper is twofold: first, to study and analyze the development phases of some past SOA based systems; second, to propose estimation metrics based on these analyzed parameters. The proposed methodology is facilitated from the use of four regression(s) based estimation models. The validation of the proposed methodology is cross checked by comparing the predictive accuracy, using some commonly used performance measurement indicators and box-plots evaluation. The evaluation results of the study (using industrial data collected from 10 SOA based software systems) show that the effort estimates obtained using the multiple linear regression model are more accurate and indicate an improvement in performance than the other used regression models.

Service ORiented Computing EnviRonment (SORCER) for deterministic global and stochastic aircraft design optimization: part 1

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones‟ algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

Service ORiented Computing EnviRonment (SORCER) for deterministic global and stochastic aircraft design optimization: part 2

Service ORiented Computing EnviRonment (SORCER) for deterministic global and stochastic aircraft design optimization: part 2

Efficient supersonic air vehicle design using the Service-Oriented Computing Environment (SORCER)

The Air Force Research Lab’s Multidisciplinary Science and Technology Center is investigating conceptual design processes and computing frameworks that could significantly impact the design of the next generation efficient supersonic air vehicle (ESAV). The ESAV conceptual design process must accommodate appropriate fidelity multidisciplinary engineering analyses (MDAs) to assess the impact of new air vehicle technologies. These analyses may be coupled and computationally expensive, posing a challenge due to the large number of air vehicle configurations analyzed during conceptual design. In light of these observations, a design process using the Service-Oriented Computing Environment (SORCER) software is implemented to combine propulsion, structures, aerodynamics, aeroelasticity, and performance in an integrated MDA. The SORCER software provides the automation and tight integration to grid computing resources necessary to achieve the volume of appropriate fidelity analyses required. Two design studies are performed using a gradient-based optimization method to produce long and short range ESAV wing designs. The studies demonstrate the capability of the ESAV MDA, the optimization algorithm, and the computational scalability and reliability of the SORCER software.

Social context-aware trust inference for trust enhancement in social network based recommendations on service providers

In Service-Oriented Computing environments, there is a large number of service providers providing a variety of services to service customers. Conventional recommender systems, which adopt the info...

An SOA-based Noise Mapping Platform for Urban Traffics

Traffic noise is a major environmental problem in many urban areas and frequently causes complaints from urban residents. An accurate traffic noise map of urban areas can facilitate noise monitoring, traffic strategic planning, street planning, residential area planning and noise prevention or reduction. An SOA based platform for urban traffic strategic noise mapping is proposed in this paper. Service Oriented Computing Environment (SORCER) is adopted to build the highly flexible distributed platform for noise monitoring and noise mapping. The platform architecture and the hierarchical services structure based on SOA are presented. The major services in the platform, including the task scheduler service, prediction service and noise propagation calculation service are analyzed in details. To demonstrate the function and mechanism of the platform, a real traffic noise mapping project for a Beijing area is presented. DOI: http://dx.doi.org/10.11591/telkomnika.v11i5.2551

Unified Mogramming with Var-Oriented Modeling and Exertion-Oriented Programming Languages

The Service ORiented Computing EnviRonment (SORCER) targets service abstractions for transdisciplinary complexity with support for heterogeneous service-oriented (SO) computing. SORCER's models are expressed in a top-down Var-oriented Modeling Language (VML) unified with programs in a bottoms-up Exertion-Oriented Language (EOL). In this paper the introduction to mogramming (modeling and programing), which uses both languages, is described. First, the emphasis is on modeling with service variables that allow for computational fidelity within VML. Then, seven types of service providers, both local and distributed, are described to form collaborative federations described in EOL. Finally, the unified hybrid of SO modeling and SO programming is presented. Fourteen simple mogramming examples illustrate the syntax and usage of both VML and EOL.

Noise Propagation Calculation Service in Urban Traffic Strategic Noise Mapping

Excessive traffic noise is a major environmental complaint in residential areas. This paper investigates a SOA based hierarchical services structure for urban traffic strategic noise mapping. Service Oriented Computing Environment (SORCER) is employed to build a highly flexible distributed platform. As the key service in our structure, Noise Propagation Calculation Service and its technical detail will be introduced. The service implements functions of sound objects generation, attenuation terms calculation and line source segmentation. The Noise Propagation Calculation Service aims to generate good-quality calculation solutions in a reasonable time. At last, this paper introduces a real traffic noise mapping project to demonstrate the service and the architecture.

Subjective Trust Inference in Composite Services

In Service-Oriented Computing (SOC) environments, the trustworthiness of each service is critical for a service client when selecting one from a large pool of services. The trust value of a service is usually in the range of [0,1] and is evaluated from the ratings given by service clients, which represent the subjective belief of these service clients on the satisfaction of delivered services. So a trust value can be taken as the subjective probability, with which one party believes that another party can perform an action in a certain situation. Hence, subjective probability theory should be adopted in trust evaluation. In addition, in SOC environments, a service usually invokes other services offered by different service providers forming a composite service. Thus, the global trust of a composite service should be evaluated based on complex invocation structures. In this paper, firstly, based on Bayesian inference, we propose a novel method to evaluate the subjective trustworthiness of a service component from a series of ratings given by service clients. Secondly, we interpret the trust dependency caused by service invocations as conditional probability, which is evaluated based on the subjective trust values of service components. Furthermore, we propose a joint subjective probability method to evaluate the subjective global trust of a composite service on the basis of trust dependency. Finally, we introduce the results of our conducted experiments to illustrate the properties of our proposed subjective global trust inference method.