DATA: Dependency-Aware Task Allocation Scheme in Distributed Edge Clouds
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Jaewook | - |
dc.contributor.author | Ko, Haneul | - |
dc.contributor.author | Kim, Joonwoo | - |
dc.contributor.author | Pack, Sangheon | - |
dc.date.accessioned | 2021-08-30T07:12:27Z | - |
dc.date.available | 2021-08-30T07:12:27Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2020-12 | - |
dc.identifier.issn | 1551-3203 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/51405 | - |
dc.description.abstract | To overcome the limitation of standalone edge cloud in terms of computing power and resource, a concept of distributed edge cloud has been introduced, where application tasks are distributed to multiple edge clouds for collaborative processing. To maximize the effectiveness of the distributed edge cloud, we formulate an optimization problem of task allocation to minimize the application completion time. To mitigate high complexity overhead in the formulated problem, we devise a low-complexity heuristic algorithm called dependency-aware task allocation (DATA) algorithm. Evaluation results demonstrate that DATA can reduce the application completion time up to by 15%-32% compared to conventional dependency-unaware task allocation schemes. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | DATA: Dependency-Aware Task Allocation Scheme in Distributed Edge Clouds | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ko, Haneul | - |
dc.contributor.affiliatedAuthor | Pack, Sangheon | - |
dc.identifier.doi | 10.1109/TII.2020.2990674 | - |
dc.identifier.scopusid | 2-s2.0-85092106536 | - |
dc.identifier.wosid | 000572631900053 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, v.16, no.12, pp.7782 - 7790 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | - |
dc.citation.title | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | - |
dc.citation.volume | 16 | - |
dc.citation.number | 12 | - |
dc.citation.startPage | 7782 | - |
dc.citation.endPage | 7790 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Industrial | - |
dc.subject.keywordAuthor | Task analysis | - |
dc.subject.keywordAuthor | Cloud computing | - |
dc.subject.keywordAuthor | Containers | - |
dc.subject.keywordAuthor | Resource management | - |
dc.subject.keywordAuthor | Optimization | - |
dc.subject.keywordAuthor | Mobile handsets | - |
dc.subject.keywordAuthor | Heuristic algorithms | - |
dc.subject.keywordAuthor | Distributed edge cloud | - |
dc.subject.keywordAuthor | heuristic algorithm | - |
dc.subject.keywordAuthor | mixed integer nonlinear program (MINLP) | - |
dc.subject.keywordAuthor | optimization | - |
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