Matches in SemOpenAlex for { <https://semopenalex.org/work/W2572583132> ?p ?o ?g. }
Showing items 1 to 61 of
61
with 100 items per page.
- W2572583132 abstract "Cloud infrastructures increasingly include a heterogeneous mix of components in terms of performance, power, and energy usage. As the size of cloud infrastructures grows, power consumption becomes a significant constraint. We use Apache Mesos and Apache Aurora, which provide massive scalability to web-scale applications, to demonstrate how a policy driven approach involving bin-packing workloads according to their power profiles, instead of the default allocation by Mesos and Aurora, can effectively reduce the peak-power and energy usage as well as the node utilization, when workloads are co-scheduled. Our experimental results show reductions of 11% in peak power, 86% for total energy usage, and an increase in utilization of 148% for memory and 8% CPU for the different policies." @default.
- W2572583132 created "2017-01-26" @default.
- W2572583132 creator A5020381188 @default.
- W2572583132 creator A5026624531 @default.
- W2572583132 creator A5049638816 @default.
- W2572583132 creator A5084367675 @default.
- W2572583132 creator A5091616971 @default.
- W2572583132 date "2016-06-01" @default.
- W2572583132 modified "2023-10-18" @default.
- W2572583132 title "Exploring the Design Space for Optimizations with Apache Aurora and Mesos" @default.
- W2572583132 cites W1977661221 @default.
- W2572583132 cites W1998252153 @default.
- W2572583132 cites W2017751491 @default.
- W2572583132 cites W2070525241 @default.
- W2572583132 cites W2102709380 @default.
- W2572583132 cites W2118651798 @default.
- W2572583132 cites W2161350347 @default.
- W2572583132 cites W2170632351 @default.
- W2572583132 cites W3005566493 @default.
- W2572583132 cites W4253704642 @default.
- W2572583132 doi "https://doi.org/10.1109/cloud.2016.0077" @default.
- W2572583132 hasPublicationYear "2016" @default.
- W2572583132 type Work @default.
- W2572583132 sameAs 2572583132 @default.
- W2572583132 citedByCount "11" @default.
- W2572583132 countsByYear W25725831322017 @default.
- W2572583132 countsByYear W25725831322018 @default.
- W2572583132 countsByYear W25725831322019 @default.
- W2572583132 countsByYear W25725831322020 @default.
- W2572583132 countsByYear W25725831322022 @default.
- W2572583132 crossrefType "proceedings-article" @default.
- W2572583132 hasAuthorship W2572583132A5020381188 @default.
- W2572583132 hasAuthorship W2572583132A5026624531 @default.
- W2572583132 hasAuthorship W2572583132A5049638816 @default.
- W2572583132 hasAuthorship W2572583132A5084367675 @default.
- W2572583132 hasAuthorship W2572583132A5091616971 @default.
- W2572583132 hasConcept C111919701 @default.
- W2572583132 hasConcept C173608175 @default.
- W2572583132 hasConcept C2778572836 @default.
- W2572583132 hasConcept C41008148 @default.
- W2572583132 hasConceptScore W2572583132C111919701 @default.
- W2572583132 hasConceptScore W2572583132C173608175 @default.
- W2572583132 hasConceptScore W2572583132C2778572836 @default.
- W2572583132 hasConceptScore W2572583132C41008148 @default.
- W2572583132 hasLocation W25725831321 @default.
- W2572583132 hasOpenAccess W2572583132 @default.
- W2572583132 hasPrimaryLocation W25725831321 @default.
- W2572583132 hasRelatedWork W1491899005 @default.
- W2572583132 hasRelatedWork W1558545464 @default.
- W2572583132 hasRelatedWork W1604898313 @default.
- W2572583132 hasRelatedWork W1975269480 @default.
- W2572583132 hasRelatedWork W2117014006 @default.
- W2572583132 hasRelatedWork W2140418760 @default.
- W2572583132 hasRelatedWork W2164287667 @default.
- W2572583132 hasRelatedWork W2372170743 @default.
- W2572583132 hasRelatedWork W2790489068 @default.
- W2572583132 hasRelatedWork W4233815414 @default.
- W2572583132 isParatext "false" @default.
- W2572583132 isRetracted "false" @default.
- W2572583132 magId "2572583132" @default.
- W2572583132 workType "article" @default.