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SERAC3: Smart and economical resource allocation for big data clusters in community clouds
SERAC3: تخصیص منابع هوشمند و اقتصادی برای خوشه های داده بزرگ در ابرهای جامعه-2018 Big data analysis jobs on clouds are gaining more and more popularity in recent years. It is critical but
challenging to pick the right configuration for an incoming job, since the configuration space is too large,
and the relationship between allocated resources and job performance is not deterministic. In this paper,
we propose SERAC3 to allocate resources smartly and economically for big data clusters in community
clouds. SERAC3 is a system that can automatically extract representative workloads from incoming big
data analysis jobs, smartly decide an optimal configuration for each job, and adjust its assigning strategy
in a quasi-realtime mode. With experiments on a community cloud built on OpenStack, we show that on
average, SERAC3 can smartly select a configuration within 2.2% of the exact optimal one, while saving
about 80.1% search cost compared to the exhaustive search.
Keywords: Resource allocation ، Big data clusters ، Representative workloads ، Community clouds |
مقاله انگلیسی |