File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Prioritized Assignment with Task Dependency in Collaborative Mobile Edge Computing

TitlePrioritized Assignment with Task Dependency in Collaborative Mobile Edge Computing
Authors
KeywordsAverage satisfaction degree
Cloud computing
Collaboration
Collaborative mobile edge computing
Delays
Monte Carlo Tree Search
Optimization
Prioritized assignment
Quality of service
Servers
Task analysis
Task dependency
Issue Date15-Jul-2024
PublisherInstitute of Electrical and Electronics Engineers
Citation
IEEE Transactions on Mobile Computing, 2024 How to Cite?
Abstract

Collaborative mobile edge computing enables resource-constrained edge facilities to work cooperatively for computation-intensive tasks. However, as the number of tasks demanded by various applications increases, resource competition is inevitable in edge facilities. Existing works tackle the resource competition problem with a first come first served (FCFS) scheme, which is blind to different delay requirements among tasks. This may result in tasks with higher delay requirements waiting a long time for service, thereby reducing overall service quality. This paper proposes a prioritized queuing scheme with task dependency (PQTD), which allows high-prioritized sub-tasks with higher delay requirements to jump into the queue ahead of low-prioritized sub-tasks with lower delay requirements. To describe the complicated delay change caused by queue-jumping, a joint DAG-queue delay (JDQD) model is proposed, which analyzes the chain reaction of delay changes caused by the processing queue on the server and the task dependency. With JDQD, a multi-task assignment optimization problem is formulated to maximize the average satisfaction degree (AvgSatD), which is defined according to the priorities of the tasks and their delay requirements. Then, a tree-based algorithm is proposed to solve the NP-hard optimization problem, i.e., Monte Carlo Tree Search (MCTS). Simulation results demonstrate the effectiveness of the PQTD queuing scheme and tree search mechanism of MCTS. Overall, PQTD + MCTS can increase AvgSatD by at least 45.8% with an acceptable complexity.


Persistent Identifierhttp://hdl.handle.net/10722/350661
ISSN
2023 Impact Factor: 7.7
2023 SCImago Journal Rankings: 2.755
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCai, Qing-
dc.contributor.authorZhou, Yiqing-
dc.contributor.authorLiu, Ling-
dc.contributor.authorQi, Yanli-
dc.contributor.authorShi, Jinglin-
dc.date.accessioned2024-11-01T00:30:21Z-
dc.date.available2024-11-01T00:30:21Z-
dc.date.issued2024-07-15-
dc.identifier.citationIEEE Transactions on Mobile Computing, 2024-
dc.identifier.issn1536-1233-
dc.identifier.urihttp://hdl.handle.net/10722/350661-
dc.description.abstract<p>Collaborative mobile edge computing enables resource-constrained edge facilities to work cooperatively for computation-intensive tasks. However, as the number of tasks demanded by various applications increases, resource competition is inevitable in edge facilities. Existing works tackle the resource competition problem with a first come first served (FCFS) scheme, which is blind to different delay requirements among tasks. This may result in tasks with higher delay requirements waiting a long time for service, thereby reducing overall service quality. This paper proposes a prioritized queuing scheme with task dependency (PQTD), which allows high-prioritized sub-tasks with higher delay requirements to jump into the queue ahead of low-prioritized sub-tasks with lower delay requirements. To describe the complicated delay change caused by queue-jumping, a joint DAG-queue delay (JDQD) model is proposed, which analyzes the chain reaction of delay changes caused by the processing queue on the server and the task dependency. With JDQD, a multi-task assignment optimization problem is formulated to maximize the average satisfaction degree (AvgSatD), which is defined according to the priorities of the tasks and their delay requirements. Then, a tree-based algorithm is proposed to solve the NP-hard optimization problem, i.e., Monte Carlo Tree Search (MCTS). Simulation results demonstrate the effectiveness of the PQTD queuing scheme and tree search mechanism of MCTS. Overall, PQTD + MCTS can increase AvgSatD by at least 45.8% with an acceptable complexity.</p>-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.relation.ispartofIEEE Transactions on Mobile Computing-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAverage satisfaction degree-
dc.subjectCloud computing-
dc.subjectCollaboration-
dc.subjectCollaborative mobile edge computing-
dc.subjectDelays-
dc.subjectMonte Carlo Tree Search-
dc.subjectOptimization-
dc.subjectPrioritized assignment-
dc.subjectQuality of service-
dc.subjectServers-
dc.subjectTask analysis-
dc.subjectTask dependency-
dc.titlePrioritized Assignment with Task Dependency in Collaborative Mobile Edge Computing -
dc.typeArticle-
dc.identifier.doi10.1109/TMC.2024.3427380-
dc.identifier.scopuseid_2-s2.0-85199074208-
dc.identifier.eissn1558-0660-
dc.identifier.isiWOS:001359244600148-
dc.identifier.issnl1536-1233-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats