Matches in SemOpenAlex for { <https://semopenalex.org/work/W3158145697> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W3158145697 endingPage "581" @default.
- W3158145697 startingPage "572" @default.
- W3158145697 abstract "Cloud data centers rely on virtualization to run a diverse set of applications. Container technology allows for a more lightweight execution, in comparison with popular Virtual Machines. Efficient scheduling of containers is still challenging due to varying request arrival patterns, application-specific resource consumption and resource heterogeneity in physical servers. Besides, containers are also more prone to resource contention and performance interference. Cloud providers need to overcome these challenges with a goal in mind: maximize resource utilization to satisfy as many requests as possible. This paper introduces RLSched, a deep reinforcement learning-based (DRL) scheduler that is self-adaptive and automatically captures the resource usage dynamics in the data center. The scheduler is based on a decentralized actor-critic multi-agent architecture that enables for parallel execution and faster convergence. RLSched relies on an enhanced network model with action shaping, which filters invalid actions and prevents the agent to fall into a sub-optimal policy. The proposed scheduler is compared against other state-of-the-art DRL methods on a simulated data center environment based on real traces from Microsoft Azure. The results show faster convergence and higher number of containers placed per session." @default.
- W3158145697 created "2021-05-10" @default.
- W3158145697 creator A5043625171 @default.
- W3158145697 creator A5089094196 @default.
- W3158145697 date "2021-01-01" @default.
- W3158145697 modified "2023-10-05" @default.
- W3158145697 title "Adaptive Container Scheduling in Cloud Data Centers: A Deep Reinforcement Learning Approach" @default.
- W3158145697 cites W1549010977 @default.
- W3158145697 cites W2602725622 @default.
- W3158145697 cites W2663975463 @default.
- W3158145697 cites W2791638009 @default.
- W3158145697 cites W2888896501 @default.
- W3158145697 cites W2905057216 @default.
- W3158145697 cites W2967841934 @default.
- W3158145697 cites W2970201418 @default.
- W3158145697 cites W3035902070 @default.
- W3158145697 cites W3094236223 @default.
- W3158145697 cites W3113924314 @default.
- W3158145697 doi "https://doi.org/10.1007/978-3-030-75078-7_57" @default.
- W3158145697 hasPublicationYear "2021" @default.
- W3158145697 type Work @default.
- W3158145697 sameAs 3158145697 @default.
- W3158145697 citedByCount "4" @default.
- W3158145697 countsByYear W31581456972022 @default.
- W3158145697 countsByYear W31581456972023 @default.
- W3158145697 crossrefType "book-chapter" @default.
- W3158145697 hasAuthorship W3158145697A5043625171 @default.
- W3158145697 hasAuthorship W3158145697A5089094196 @default.
- W3158145697 hasConcept C111919701 @default.
- W3158145697 hasConcept C120314980 @default.
- W3158145697 hasConcept C127413603 @default.
- W3158145697 hasConcept C153740404 @default.
- W3158145697 hasConcept C154945302 @default.
- W3158145697 hasConcept C206729178 @default.
- W3158145697 hasConcept C21547014 @default.
- W3158145697 hasConcept C25344961 @default.
- W3158145697 hasConcept C31258907 @default.
- W3158145697 hasConcept C41008148 @default.
- W3158145697 hasConcept C513985346 @default.
- W3158145697 hasConcept C79974875 @default.
- W3158145697 hasConcept C93996380 @default.
- W3158145697 hasConcept C97541855 @default.
- W3158145697 hasConceptScore W3158145697C111919701 @default.
- W3158145697 hasConceptScore W3158145697C120314980 @default.
- W3158145697 hasConceptScore W3158145697C127413603 @default.
- W3158145697 hasConceptScore W3158145697C153740404 @default.
- W3158145697 hasConceptScore W3158145697C154945302 @default.
- W3158145697 hasConceptScore W3158145697C206729178 @default.
- W3158145697 hasConceptScore W3158145697C21547014 @default.
- W3158145697 hasConceptScore W3158145697C25344961 @default.
- W3158145697 hasConceptScore W3158145697C31258907 @default.
- W3158145697 hasConceptScore W3158145697C41008148 @default.
- W3158145697 hasConceptScore W3158145697C513985346 @default.
- W3158145697 hasConceptScore W3158145697C79974875 @default.
- W3158145697 hasConceptScore W3158145697C93996380 @default.
- W3158145697 hasConceptScore W3158145697C97541855 @default.
- W3158145697 hasLocation W31581456971 @default.
- W3158145697 hasOpenAccess W3158145697 @default.
- W3158145697 hasPrimaryLocation W31581456971 @default.
- W3158145697 hasRelatedWork W2001641920 @default.
- W3158145697 hasRelatedWork W2070754358 @default.
- W3158145697 hasRelatedWork W2076590219 @default.
- W3158145697 hasRelatedWork W2169739900 @default.
- W3158145697 hasRelatedWork W2182227208 @default.
- W3158145697 hasRelatedWork W2538603934 @default.
- W3158145697 hasRelatedWork W3018860200 @default.
- W3158145697 hasRelatedWork W3114501693 @default.
- W3158145697 hasRelatedWork W4301397976 @default.
- W3158145697 hasRelatedWork W4382897111 @default.
- W3158145697 isParatext "false" @default.
- W3158145697 isRetracted "false" @default.
- W3158145697 magId "3158145697" @default.
- W3158145697 workType "book-chapter" @default.