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In "Relay deployment" section, the scenario for relaying is discussed.
The structure provided through ChemicalTagger facilitates these inferences (see the 'Architecture and Deployment' section).
The "Removing vulnerabilities: before deployment" section presents some discussion on other ways that might be used for removing vulnerabilities before the system is deployed.
The structure of the database has three branches: section dedicated to describing the instruments, their characteristics, and their position (deployment); section used to store data and related metadata (measurements); section reserved to store the vocabularies used to standardize data and metadata and the data used by quality control algorithms (common vocabularies and quality control).
section dedicated to describing the instruments, their characteristics, and their position (deployment); section used to store data and related metadata (measurements); section reserved to store the vocabularies used to standardize data and metadata and the data used by quality control algorithms (common vocabularies and quality control).
In particular: We separated the performance experiments from the deployment section.
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BID schemes are designed taking into consideration the requirements laid out earlier in "Requirements from a block I/O scheduler in Big Data deployments" section.
BID is aimed to avoid contention following system constraints without compromising SLAs, as described in "Requirements from a block I/O scheduler in Big Data deployments" section.
"Requirements from a block I/O scheduler in Big Data deployments" section lays down the expectation from a block I/O scheduler in Big Data deployments as well as points out the issues with the current Linux scheduling schemes.
We observe that the existing Block I/O schedulers do not support the set of requirements laid down in "Requirements from a block I/O scheduler in Big Data deployments" section and there is a clear need of new I/O scheduling scheme for such Big Data deployments.
"Hadoop MapReduce: working and workload characteristics" and "Requirements from a block I/O scheduler in Big Data deployments" sections discuss the I/O workload characteristics of Hadoop deployments and the requirements from a I/O scheduler in such environments, respectively.
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