Titlebook: Quantitative Evaluation of Systems; 18th International C Alessandro Abate,Andrea Marin Conference proceedings 2021 Springer Nature Switzerl

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Performance Evaluation: Model-Driven or?Problem-Driven?ign. After looking back briefly on the history of the field, I subsequently reflect on the reasons why the field of performance evaluation has become so isolated. I then continue with a set of eight recommendations, based on my experience in performing projects with industry, that will help in recon

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A Modest Approach to Dynamic Heuristic Search in Probabilistic Model Checkingning context. Its core functionality is based on enhancements of the heuristic search methods . and . and is capable of handling efficiently maximal and minimal reachability properties, expected reward properties as well as bounded properties on general MDPs. . is integrated in the infrastructure of

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Tweaking the Odds in Probabilistic Timed Automatareal-time systems where exact probabilities are unknown, or where the probability values should be optimised. We prove that existing techniques to transform probabilistic timed automata into equivalent finite-state Markov decision processes (MDPs) remain correct in the parametric setting, using a sy

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Vital-Signs

Postmenopause

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SEH: Size Estimate Hedging for Single-Server Queueserver system when exact information about the jobs’ processing times is not available. When the SRPT policy uses estimated processing times, the underestimation of large jobs can significantly degrade performance. We propose a simple heuristic, Size Estimate Hedging (SEH), that only uses estimated p

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An Approximate Bribe Queueing Model for Bid Advising in Cloud Spot Marketsirements, along with a bid value. Jobs are preemptively ordered based on their bid values as the available capacity, which is excess capacity made available for the spot market, may vary over time. Due to this variation, the number of allocated containers to a job may vary during its lifetime, resul