Port-Based Reliability Computing for Service Composition

Ding, Zuohua; Jiang, Mingyue; Kandel, A.

doi:10.1109/tsc.2011.17

Cited by 18 publications

(7 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various approaches have been proposed to handle the problem of dynamic composition of Web services [5], [26], [30]; however, most of these approaches are based on centralized mechanisms. These centralized mechanisms become impractical in scenarios with dynamic arrivals and departures of service providers, which require frequent updating of the central entities, resulting in a huge system overhead.…”

Section: Related Work and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Trustworthy Stigmergic Service Compositionand Adaptation in Decentralized Environments

Moustafa

Zhang

Bai

2016

IEEE Trans. Serv. Comput.

View full text Add to dashboard Cite

The widespread use of web services in forming complex online applications requires service composition to cope with highly dynamic and heterogeneous environments. Traditional centralized service composition techniques are not sufficient to address the needs of applications in decentralized environments. In this paper, a stigmergic-based approach is proposed to model the decentralized service interactions and handle service composition in highly dynamic open environments. In the proposed approach, web services and resources are modeled as multiple agents. Stigmergic-based self-organization mechanisms among agents are deployed to facilitate adapting service composition. In addition, to overcome the limitations of traditional QoS-based approaches, trust measurements are deployed as a criterion for service selection. To improve the performance of the proposed stigmergic-based approach under dynamic scale-free environments, we investigate the hybridization with local search operators to consolidate adaptation, and diversity schemes are introduced to facilitate continual service adaptation. Extensive experiments show the efficiency of the proposed approach in dealing with incomplete information and dynamic factors in composing and adapting web services in open environments. The experiment results also show that the proposed approach achieves a better performance than other traditional approaches.

show abstract

Section: Related Work and Discussionmentioning

confidence: 99%

“…Many approaches have been proposed in the literature to tackle web service composition and adaptation [5], [30]. Most of them, however, assume a centralized composition environment.…”

Section: Introductionmentioning

confidence: 99%

Trustworthy Stigmergic Service Compositionand Adaptation in Decentralized Environments

Moustafa

Zhang

Bai

2016

IEEE Trans. Serv. Comput.

View full text Add to dashboard Cite

show abstract

“…In our previous work [3] we developed a port based reliability model for measuring online reliability of composite services. We applied a component based design model, namely Service Component Architecture (SCA).…”

Section: Port Based Component Model For Service Compositionmentioning

confidence: 99%

Online reliability prediction of service composition

Ding

Chen

2014

Proceedings of the 2014 3rd International Workshop on Evidential Assessment of Software Technologies

Self Cite

View full text Add to dashboard Cite

Reliability is an important quality attribute for service oriented software. Existing approaches use static data collected from the testing to predict the software reliability. These approaches do not address the dynamism of service behavior after deployment. In this paper, we propose a method from any time moment to predict reliability of service composition in the near future. We first collect the service runtime data to predict the future failure data by using the ARIMA model. We then predict the reliability of each port based on the Nelson model, and finally we can compute the reliability of composite services. An Online Shop example is used to demonstrate the effectiveness of our method.

show abstract

“…Among the properties of QoS, the reliability is very important in a dynamic environment. The reliability of service composition can be computed on the basis of Service Component Architecture [29]. Aggregated reliability [6,30] is proposed to maximize the chance to successfully execute the remaining operations, but the other properties are not considered in its corresponding selection method.…”

Section: Related Work and Comparison Analysismentioning

confidence: 99%

An adaptive service selection method for cross‐cloud service composition

Yang

Lin

Dou

2013

Concurrency and Computation

View full text Add to dashboard Cite

SUMMARY Cloud computing aims at providing elastic applications that can be scaled at runtime. In practice, traditional service composition methods are not flexible enough to changes in cross‐cloud environment. In view of this challenge, an adaptive service selection method for cross‐cloud service composition is proposed in this paper, by dynamically selecting proper services with near‐optimal performance for adapting to changes in time. First, concretely speaking, the service selection and execution are modeled with Markov decision process to ensure flexibility. Second, service pair is defined, and the way to build service pairs set is proposed to predict the performance of candidate services. Third, the adaptive service selection algorithm is designed to select proper cloud services for changing cross‐cloud environment. Finally, a case study for cross‐cloud service composition and experiments are presented for validating the feasibility of our proposal. Concurrency and Computation: Practice and Experience, 2013.© 2013 Wiley Periodicals, Inc.

show abstract

Port-Based Reliability Computing for Service Composition

Cited by 18 publications

References 34 publications

Trustworthy Stigmergic Service Compositionand Adaptation in Decentralized Environments

Trustworthy Stigmergic Service Compositionand Adaptation in Decentralized Environments

Online reliability prediction of service composition

An adaptive service selection method for cross‐cloud service composition

Contact Info

Product

Resources

About