In a service-oriented architecture (SOA), a service broker assigns a previously published service (stored in a service registry) to a service requester. It is desirable for the composition of the requesting and the assigned service to interact properly. While proper interaction is often reduced to deadlock freedom of the composed system, we additionally consider livelock freedom as a desirable property for the interaction of services. In principle, deadlock-and livelock freedom can be verified by inspecting the state space of the composition of (public views of) the involved services.The contribution of this paper is to propose a methodology to build that state space from pre-computed fragments which are computed upon publishing a service. That way, we shift computation time from the time critical "request" phase of service brokerage to the less critical "publish" phase. Interestingly, our setting enables state space reduction methods that are intrinsically different from traditional state space reductions.
A big issue in the paradigm of Service Oriented Architectures (SOA) is service discovery. Organizations publish their services via the Internet. These published services can then be automatically found and accessed by other services, meaning, the services are composed. A fundamental property of a service composition is weak termination, which guarantees the absence of deadlocks and livelocks. In principle, weak termination can be verified by inspecting the state space of the composition of (public views of) the involved services. We propose a methodology to build that state space from precomputed fragments, which are computed upon publishing a service. That way, we shift computation effort from the resource critical “find” phase to the less critical “publish” phase. Interestingly, our setting enables state space reduction methods that are intrinsically different from traditional state space reductions. We further show the positive impact of our approach to the computational effort of service discovery.
The ordinary variable inspection plans rely on the normality of the underlying populations. However, this assumption is vague or even not satisfied. Moreover, ordinary variable sampling plans are sensitive against deviations from the distribution assumption.Nonconforming items occur in the tails of the distribution. They can be approximated by a Generalized Pareto distribution (GPD). We investigate several estimates of their parameters according to their usefulness not only for the GPD, but also for arbitrary continuous distributions. The Likelihood Moment estimates (LME) of Zhang (2007) and the Bayesian estimate (ZSE) of Zhang and Stephens (2009) turn out to be the best for our purpose. Then we use these parameter estimates to estimate the fraction defective.The asymptotic normality of the LME (cf. Zhang, 2007) and of the fraction defective are used to construct the sampling plan. The difference to the sampling plans constructed in Kössler (1999Kössler ( , 2015 is that we now use the new parameter estimates. Moreover, in contrast to the aforementioned papers, we now also consider two-sided specification limits.An industrial example illustrates the method.
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