Abstract. In service networks, discovery plays a crucial role as a layer where providers can be published and enumerated. This work focuses on the responsiveness of the discovery layer, the probability to operate successfully within a deadline, even in the presence of faults. It proposes a hierarchy of stochastic models for decentralized discovery and uses it to describe the discovery of a single service using three popular protocols. A methodology to use the model hierarchy in wireless mesh networks is introduced. Given a pair requester and provider, a discovery protocol and a deadline, it generates specific model instances and calculates responsiveness. Furthermore, this paper introduces a new metric, the expected responsiveness distance der, to estimate the maximum distance from a provider where requesters can still discover it with a required responsiveness. Using monitoring data from the DES testbed at Freie Universität Berlin, it is shown how responsiveness and der of the protocols change depending on the position of nodes and the link qualities in the network.
An ever-increasing number of both functional and non-functional requirements has resulted in growing system complexity which demands new solutions in system modeling and evaluation. As a remedy, service-oriented architecture (SOA) offers services as basic building elements of system design. Service dependability is highly dependent on the properties of the underlying information and communications technology (ICT) infrastructure. This is especially true for the user-perceived dependability of a specific pair service client and provider as every pair may utilize different ICT components.We provide a model for the description of ICT components and their non-functional properties based on the Unified Modeling Language (UML). Given a service description, a network topology model and a pair service client and provider, we propose a methodology to automatically identify relevant ICT components and generate a user-perceived service infrastructure model (UPSIM). We demonstrate the feasibility of the methodology by applying it to parts of the service network infrastructure at University of Lugano (USI), Switzerland. We then show how this methodology can be used to facilitate userperceived service dependability analysis.
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