446 research outputs found

    Experimental Assembly and Sterilization Laboratory - Clothing study

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    Effect of clothing on control of microorganism shedding from worker constructing printed circuit board assembl

    Study of chemical germicides

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    Chemical germicides as decontamination agents for spacecraft sterilizatio

    Sterilization Assembly Development Laboratory - Routine cleaning and decontamination of the SADL facility

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    Procedures for preparing cleaning and germicidal solutions and cleaning equipment for spacecraft sterilizatio

    How to Overcome an Anti-democratic Heritage

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    Effectiveness of utilizing assay coupons for biological load prediction

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    Bioassay coupons for predicting biological loads and contamination following exposure to vertical laminar flo

    UpStream: storage-centric load management for streaming applications with update semantics

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    This paper addresses the problem of minimizing the staleness of query results for streaming applications with update semantics under overload conditions. Staleness is a measure of how out-of-date the results are compared with the latest data arriving on the input. Real-time streaming applications are subject to overload due to unpredictably increasing data rates, while in many of them, we observe that data streams and queries in fact exhibit "update semantics” (i.e., the latest input data are all that really matters when producing a query result). Under such semantics, overload will cause staleness to build up. The key to avoid this is to exploit the update semantics of applications as early as possible in the processing pipeline. In this paper, we propose UpStream, a storage-centric framework for load management over streaming applications with update semantics. We first describe how we model streams and queries that possess the update semantics, providing definitions for correctness and staleness for the query results. Then, we show how staleness can be minimized based on intelligent update key scheduling techniques applied at the queue level, while preserving the correctness of the results, even for complex queries that involve sliding windows. UpStream is based on the simple idea of applying the updates in place, yet with great returns in terms of lowering staleness and memory consumption, as we also experimentally verify on the Borealis syste
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