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Baek, Woongki
Intelligent System Software Lab.
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dc.citation.endPage 1882 -
dc.citation.number 4 -
dc.citation.startPage 1868 -
dc.citation.title IEEE TRANSACTIONS ON SERVICES COMPUTING -
dc.citation.volume 15 -
dc.contributor.author Han, Myeonggyun -
dc.contributor.author Baek, Woongki -
dc.date.accessioned 2023-12-21T14:07:16Z -
dc.date.available 2023-12-21T14:07:16Z -
dc.date.created 2021-01-13 -
dc.date.issued 2022-07 -
dc.description.abstract Workload consolidation is a widely-used technique to improve the resource utilization of services computing systems by consolidating latency-critical (LC) and batch workloads on the same physical server. The resource manager for workload consolidation dynamically allocates hardware resources (e.g., cores, caches) to the workloads to maximize the resource utilization while satisfying the service-level objective (SLO) of the LC workloads. Since security-critical hardware resources are dynamically allocated across consolidated workloads, information leakages can be created among workloads through microarchitectural side-channel (SC) attacks. Despite extensive prior works, it is yet to investigate efficient system software support for achieving high resource utilization without compromising the SLO and security of consolidated workloads. To bridge this gap, we propose SDRP, secure and dynamic resource partitioning for safe, efficient, and SLO-aware workload consolidation. As with the state-of-the-art techniques, SDRP dynamically allocates hardware resources to enhance the resource utilization and provide the SLO guarantees. In contrast to the state-of-the-art techniques, SDRP dynamically sanitizes security-critical hardware resources to robustly defeat microarchitectural SC attacks. Our quantitative evaluation demonstrates that SDRP achieves high resource sanitization quality, introduces low performance overheads, delivers high resource utilization with the SLO and security guarantees, and defeats the last-level cache (LLC)-based SC attack. -
dc.identifier.bibliographicCitation IEEE TRANSACTIONS ON SERVICES COMPUTING, v.15, no.4, pp.1868 - 1882 -
dc.identifier.doi 10.1109/TSC.2020.3024552 -
dc.identifier.issn 1939-1374 -
dc.identifier.scopusid 2-s2.0-85091269072 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/49511 -
dc.identifier.url https://ieeexplore.ieee.org/document/9200560 -
dc.identifier.wosid 000836642800009 -
dc.language 영어 -
dc.publisher Institute of Electrical and Electronics Engineers -
dc.title SDRP: Safe, Efficient, and SLO-Aware Workload Consolidation through Secure and Dynamic Resource Partitioning -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.relation.journalWebOfScienceCategory Computer Science, Information Systems;Computer Science, Software Engineering -
dc.relation.journalResearchArea Computer Science -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Hardware -
dc.subject.keywordAuthor Containers -
dc.subject.keywordAuthor Security -
dc.subject.keywordAuthor Microarchitecture -
dc.subject.keywordAuthor Resource management -
dc.subject.keywordAuthor Dynamic scheduling -
dc.subject.keywordAuthor Virtualization -
dc.subject.keywordAuthor Resource partitioning -
dc.subject.keywordAuthor server consolidation -
dc.subject.keywordAuthor security -
dc.subject.keywordAuthor efficiency -
dc.subject.keywordAuthor service-level objective -

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