FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2067220670> ?p ?o ?g. }

• W2067220670 abstract "In MapReduce, placing computation near its input data is considered to be desirable since otherwise the data transmission introduces an additional delay to the task execution. This data locality problem has been studied in the literature. Most existing scheduling algorithms in MapReduce focus on improving performance through increasing locality. In this paper, we view the data locality problem from a network perspective. The key observation is that if we make appropriate use of the network to route the data chunk to the machine where it will be processed in advance, then processing a remote task is the same as processing a local task. In other words, instead of bringing computation close to data, we can also bring data close to computation to improve the system performance. However, to benefit from such a strategy, we must (i) balance the tasks assigned to local machines and those assigned to remote machines, and (ii) design the routing algorithm to avoid network congestion. Taking these challenges into consideration, we propose a scheduling/routing algorithm, named the Joint Scheduler, which utilizes both the computing resources and the communication network efficiently. To show that the Joint Scheduler has superior performance, we prove that the Join Scheduler can support any load that can be supported by some other algorithm, i.e., achieve the maximum capacity region. Simulation results demonstrate that with popularity skew, the Joint Scheduler improves the throughput significantly (more than 30% in our simulations) compared to the Hadoop Fair Scheduler with delay scheduling, which is the de facto industry standard. The delay performance is also evaluated through simulations, where we can see a significant delay reduce under the Joint Scheduler with moderate to heavy load." @default.
• W2067220670 created "2016-06-24" @default.
• W2067220670 creator A5023440365 @default.
• W2067220670 creator A5025956941 @default.
• W2067220670 date "2014-09-01" @default.
• W2067220670 modified "2023-10-16" @default.
• W2067220670 title "Data locality in MapReduce: A network perspective" @default.
• W2067220670 cites W1973650525 @default.
• W2067220670 cites W1985790218 @default.
• W2067220670 cites W2022678927 @default.
• W2067220670 cites W2045717006 @default.
• W2067220670 cites W2060204338 @default.
• W2067220670 cites W2094469165 @default.
• W2067220670 cites W2096125134 @default.
• W2067220670 cites W2105177639 @default.
• W2067220670 cites W2119565742 @default.
• W2067220670 cites W2119738171 @default.
• W2067220670 cites W2132353061 @default.
• W2067220670 cites W2157099238 @default.
• W2067220670 cites W2173213060 @default.
• W2067220670 cites W3142851257 @default.
• W2067220670 cites W4238465620 @default.
• W2067220670 doi "https://doi.org/10.1109/allerton.2014.7028579" @default.
• W2067220670 hasPublicationYear "2014" @default.
• W2067220670 type Work @default.
• W2067220670 sameAs 2067220670 @default.
• W2067220670 citedByCount "8" @default.
• W2067220670 countsByYear W20672206702015 @default.
• W2067220670 countsByYear W20672206702017 @default.
• W2067220670 countsByYear W20672206702018 @default.
• W2067220670 countsByYear W20672206702019 @default.
• W2067220670 countsByYear W20672206702020 @default.
• W2067220670 countsByYear W20672206702021 @default.
• W2067220670 crossrefType "proceedings-article" @default.
• W2067220670 hasAuthorship W2067220670A5023440365 @default.
• W2067220670 hasAuthorship W2067220670A5025956941 @default.
• W2067220670 hasConcept C12713177 @default.
• W2067220670 hasConcept C138885662 @default.
• W2067220670 hasConcept C154945302 @default.
• W2067220670 hasConcept C2779808786 @default.
• W2067220670 hasConcept C41008148 @default.
• W2067220670 hasConcept C41895202 @default.
• W2067220670 hasConceptScore W2067220670C12713177 @default.
• W2067220670 hasConceptScore W2067220670C138885662 @default.
• W2067220670 hasConceptScore W2067220670C154945302 @default.
• W2067220670 hasConceptScore W2067220670C2779808786 @default.
• W2067220670 hasConceptScore W2067220670C41008148 @default.
• W2067220670 hasConceptScore W2067220670C41895202 @default.
• W2067220670 hasLocation W20672206701 @default.
• W2067220670 hasOpenAccess W2067220670 @default.
• W2067220670 hasPrimaryLocation W20672206701 @default.
• W2067220670 hasRelatedWork W1498362922 @default.
• W2067220670 hasRelatedWork W1510550274 @default.
• W2067220670 hasRelatedWork W1523525818 @default.
• W2067220670 hasRelatedWork W1548317368 @default.
• W2067220670 hasRelatedWork W1585932355 @default.
• W2067220670 hasRelatedWork W2363648756 @default.
• W2067220670 hasRelatedWork W2381880241 @default.
• W2067220670 hasRelatedWork W2626799276 @default.
• W2067220670 hasRelatedWork W2886384632 @default.
• W2067220670 hasRelatedWork W2972273479 @default.
• W2067220670 isParatext "false" @default.
• W2067220670 isRetracted "false" @default.
• W2067220670 magId "2067220670" @default.
• W2067220670 workType "article" @default.