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Majority voting among replicated data collection devices enhances the trust-worthiness of data flowing from a hostile external environment. It allows a correct data fusion and dissemination by the end-users, in the presence of content corruptions and/or timing failures that may possibly occur during data collection. In addition, a device may operate on fuzzy inputs, thereby generating a data that occasionally deviates from the reference datum in physical world. In this paper, we provide a QoS-oriented approach to manage the data flow through various system elements. The application-level QoS parameters we consider are timeliness and accuracy of data. The underlying protocol-level parameters that influence data delivery performance are the data sizes, network bandwidth, device asynchrony, and data fuzziness. A replica voting protocol takes into account the interplay between these parameters as the faulty behavior of malicious devices unfolds in various forms during data collection. Our QoS-oriented approach casts the well-known fault-tolerance techniques, namely, 2-phase voting, with control mechanisms that adapt the data delivery to meet the end-to-end constraints - such as latency, data integrity, and resource cost. The paper describes a middleware architecture to realize our QoS-oriented approach to the management of replicated data flows.