Matches in SemOpenAlex for { <https://semopenalex.org/work/W2998498679> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W2998498679 endingPage "3329" @default.
- W2998498679 startingPage "3319" @default.
- W2998498679 abstract "Vehicle fog computing (VFC) is proposed as a solution that can significantly reduce the task processing overload of base station during the peak time, where the vehicle as a fog node contributes idle computing resource for task processing. However, there are still many challenges in the deployment of VFC, such as the lack of specific incentives of resource contribution, high system complexity, and offloading collisions between vehicles when the vehicles are offloading tasks simultaneously. In this paper, we first propose a novel contract-based incentive mechanism that combines resource contribution and resource utilization. Based on that, we propose to use distributed deep reinforcement learning to allocate resources and reduce system complexity. Task offloading method based on the queuing model is also proposed to avoid decision collisions in multi-vehicles task offloading. Numerical experiment results demonstrate that our proposed scheme has achieved a significant improvement in task offloading and resource allocation performance." @default.
- W2998498679 created "2020-01-10" @default.
- W2998498679 creator A5022515398 @default.
- W2998498679 creator A5042261970 @default.
- W2998498679 creator A5059379627 @default.
- W2998498679 creator A5085078614 @default.
- W2998498679 date "2020-01-01" @default.
- W2998498679 modified "2023-10-12" @default.
- W2998498679 title "Contract-Based Computing Resource Management via Deep Reinforcement Learning in Vehicular Fog Computing" @default.
- W2998498679 cites W1590174667 @default.
- W2998498679 cites W2021330138 @default.
- W2998498679 cites W2216435223 @default.
- W2998498679 cites W2343050074 @default.
- W2998498679 cites W2397723600 @default.
- W2998498679 cites W2514619461 @default.
- W2998498679 cites W2546571074 @default.
- W2998498679 cites W2588977989 @default.
- W2998498679 cites W2620831508 @default.
- W2998498679 cites W2735764544 @default.
- W2998498679 cites W2741401130 @default.
- W2998498679 cites W2741912721 @default.
- W2998498679 cites W2754272363 @default.
- W2998498679 cites W2761862361 @default.
- W2998498679 cites W2782921900 @default.
- W2998498679 cites W2786309777 @default.
- W2998498679 cites W2789986657 @default.
- W2998498679 cites W2792526074 @default.
- W2998498679 cites W2796934112 @default.
- W2998498679 cites W2913196913 @default.
- W2998498679 cites W2914289538 @default.
- W2998498679 cites W2921417096 @default.
- W2998498679 cites W2954039338 @default.
- W2998498679 cites W2955408070 @default.
- W2998498679 cites W2957938917 @default.
- W2998498679 cites W2963000651 @default.
- W2998498679 cites W2963334314 @default.
- W2998498679 cites W2963361189 @default.
- W2998498679 cites W2966753637 @default.
- W2998498679 cites W2969324740 @default.
- W2998498679 cites W2979897999 @default.
- W2998498679 cites W2980360843 @default.
- W2998498679 cites W2980970610 @default.
- W2998498679 cites W2996977605 @default.
- W2998498679 doi "https://doi.org/10.1109/access.2019.2963051" @default.
- W2998498679 hasPublicationYear "2020" @default.
- W2998498679 type Work @default.
- W2998498679 sameAs 2998498679 @default.
- W2998498679 citedByCount "38" @default.
- W2998498679 countsByYear W29984986792020 @default.
- W2998498679 countsByYear W29984986792021 @default.
- W2998498679 countsByYear W29984986792022 @default.
- W2998498679 countsByYear W29984986792023 @default.
- W2998498679 crossrefType "journal-article" @default.
- W2998498679 hasAuthorship W2998498679A5022515398 @default.
- W2998498679 hasAuthorship W2998498679A5042261970 @default.
- W2998498679 hasAuthorship W2998498679A5059379627 @default.
- W2998498679 hasAuthorship W2998498679A5085078614 @default.
- W2998498679 hasBestOaLocation W29984986791 @default.
- W2998498679 hasConcept C120314980 @default.
- W2998498679 hasConcept C154945302 @default.
- W2998498679 hasConcept C2780609101 @default.
- W2998498679 hasConcept C2986652147 @default.
- W2998498679 hasConcept C38652104 @default.
- W2998498679 hasConcept C41008148 @default.
- W2998498679 hasConcept C81860439 @default.
- W2998498679 hasConcept C97541855 @default.
- W2998498679 hasConceptScore W2998498679C120314980 @default.
- W2998498679 hasConceptScore W2998498679C154945302 @default.
- W2998498679 hasConceptScore W2998498679C2780609101 @default.
- W2998498679 hasConceptScore W2998498679C2986652147 @default.
- W2998498679 hasConceptScore W2998498679C38652104 @default.
- W2998498679 hasConceptScore W2998498679C41008148 @default.
- W2998498679 hasConceptScore W2998498679C81860439 @default.
- W2998498679 hasConceptScore W2998498679C97541855 @default.
- W2998498679 hasFunder F4320321001 @default.
- W2998498679 hasFunder F4320321540 @default.
- W2998498679 hasFunder F4320324856 @default.
- W2998498679 hasLocation W29984986791 @default.
- W2998498679 hasLocation W29984986792 @default.
- W2998498679 hasOpenAccess W2998498679 @default.
- W2998498679 hasPrimaryLocation W29984986791 @default.
- W2998498679 hasRelatedWork W1485627940 @default.
- W2998498679 hasRelatedWork W1494335708 @default.
- W2998498679 hasRelatedWork W1568263432 @default.
- W2998498679 hasRelatedWork W2113059852 @default.
- W2998498679 hasRelatedWork W2152433827 @default.
- W2998498679 hasRelatedWork W2900070427 @default.
- W2998498679 hasRelatedWork W3094198577 @default.
- W2998498679 hasRelatedWork W4213446031 @default.
- W2998498679 hasRelatedWork W4285983629 @default.
- W2998498679 hasRelatedWork W4313532196 @default.
- W2998498679 hasVolume "8" @default.
- W2998498679 isParatext "false" @default.
- W2998498679 isRetracted "false" @default.
- W2998498679 magId "2998498679" @default.
- W2998498679 workType "article" @default.