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Partitioning Kernel with Capability Controlled Temporal and Spatial Partitioning
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Theoretical Computer Science, TCS.ORCID iD: 0000-0002-7355-4288
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Theoretical Computer Science, TCS.ORCID iD: 0000-0002-8069-6495
2025 (English)In: 2025 IEEE Real-Time Systems Symposium, RTSS, Institute of Electrical and Electronics Engineers (IEEE) , 2025, p. 68-81Conference paper, Published paper (Refereed)
Abstract [en]

Partitioning kernels often face challenges such as static resource allocation and insufficient temporal protection, limiting their applicability in dynamic and mixed-criticality systems where resource needs and security boundaries evolve over time. To address these limitations, we present S3K, a capability-based multicore partitioning kernel for embedded RISC-V systems. S3K provides robust spatial and temporal isolation, time protection, and dynamic resource reconfiguration, enabling flexible adaptation to changing operational requirements while maintaining strong safety and security guarantees. Its capability-based model ensures secure and efficient resource management, while in-kernel data partitioning prevents information leakage and mitigates side-channel attacks. Additionally, S3K's scheduler guarantees deterministic process dispatch, free from microarchitectural interference. Evaluation results demonstrate S3K's effectiveness, showing the absence of scheduling jitter, resistance to intra-core side-channels, and efficient inter-process communication. These results highlight S3K's suitability for safety-critical and security-critical applications in dynamic, resource-constrained environments.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2025. p. 68-81
Series
Real-Time Systems Symposium-Proceedings, ISSN 1052-8725
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-380632DOI: 10.1109/RTSS66672.2025.00015ISI: 001679922100006Scopus ID: 2-s2.0-105032428671OAI: oai:DiVA.org:kth-380632DiVA, id: diva2:2060520
Conference
46th Real Time Systems Symposium-RTSS-Annual, DEC 02-05, 2025, Boston, MA, USA
Note

Part of ISBN 9798331596439, 9798331596422

QC 20260716

Available from: 2026-05-18 Created: 2026-05-18 Last updated: 2026-07-16Bibliographically approved

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Karlsson, Henrik A.Guanciale, Roberto

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