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Bozheng Liu

dblp:268/9481 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 81% Cloud and datacenter computing · 19%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Embedded and real-time systems › real-time scheduling › pre-run-time scheduling
cyclic scheduling
0.612022
Regularity-Based Virtualization Under the ARINC 653 Standard for Embedded Systems · IEEE Trans. Computers 2022
Embedded and real-time systems › real-time scheduling
multicore scheduling
0.612022
Regularity-Based Virtualization Under the ARINC 653 Standard for Embedded Systems · IEEE Trans. Computers 2022
Embedded and real-time systems
real-time scheduling
0.612022
Regularity-Based Virtualization Under the ARINC 653 Standard for Embedded Systems · IEEE Trans. Computers 2022
Embedded and real-time systems
real-time virtualization
0.612022
Regularity-Based Virtualization Under the ARINC 653 Standard for Embedded Systems · IEEE Trans. Computers 2022
Cloud and datacenter computing › resource allocation › resource allocation policy
resource partitioning
0.612022
Regularity-Based Virtualization Under the ARINC 653 Standard for Embedded Systems · IEEE Trans. Computers 2022

Methods — techniques the papers use, named apart from their topics

optimal scheduling · 0.6approximation algorithm · 0.6
YearPublicationVenuePosition
2022 Regularity-Based Virtualization Under the ARINC 653 Standard for Embedded Systems
abstract
In embedded real-time virtualized systems (ERTVS), the ARINC 653 standard specifies a cyclic scheduling policy to guarantee the real-time performance of tasks in multiple Virtual Machines (VMs) residing on shared hardware. Based on this policy, the Regularity-based Resource Partitioning (RRP) model defines an efficient interface specification to hierarchically partition and assign resource slices among VMs. Although this model has received plenty of attention recently, three major pieces remain missing for applying this model in ERTVS. (1) Embedded systems are more sensitive to resource utilization efficiency since this may drastically affect their deployment cost for including additional cores. Therefore, this paper proposes an optimal and an approximate RRP resource scheduler for multi-core platforms. (2) A resource reconfiguration is required when an embedded system has to switch between operating modes, resulting in the current cyclic schedule being replaced by another pre-configured and verified cyclic schedule. This paper formalizes a new One-Hop Reconfiguration (OHR) problem tailored for mode-switch-capable embedded systems and introduces a corresponding optimal solution. (3) No RRP-based toolset is currently available for embedded systems. This paper thus presents an optimized RRP toolset tailored for embedded systems. Numerous experiments are conducted to evaluate the efficacy of this toolset.
Guangli Dai, Pavan Kumar Paluri, Albert Mo Kim Cheng, Bozheng Liu
IEEE Trans. Computers4