Tiwei Bie

dblp:378/5828 · DBLP profile ↗
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4ranked-venue papers
0as first author
4since 2021 · last 2026
—ORCID · conflict

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

Systems, architecture and hardware · 3 · 3 since 2021Software engineering, systems software and programming languages · 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
4 papers
Cloud and datacenter computing · 92% Parallel and multicore computing · 8%
Software engineering, system software, and programming languages
1 paper
Operating systems · 100%

Topics — the 15 heaviest of 15, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
virtualization
2.022026
DCS3: A Dual-Layer Co-Aware Scheduler With Stealing Balance and Synchronized Priority in Virtualization Environments · IEEE Trans. Computers 2026
SKernel: An Elastic and Efficient Secure Container System at Scale with a Split-Kernel Architecture · EuroSys 2026
Operating systems › system security › operating system security › protection mechanism › isolation
kernel isolation
1.012026
SKernel: An Elastic and Efficient Secure Container System at Scale with a Split-Kernel Architecture · EuroSys 2026
Cloud and datacenter computing › cluster resource management and scheduling › resource scheduling
cross-layer scheduling
1.012026
DCS3: A Dual-Layer Co-Aware Scheduler With Stealing Balance and Synchronized Priority in Virtualization Environments · IEEE Trans. Computers 2026
Parallel and multicore computing
load balancing
1.012026
DCS3: A Dual-Layer Co-Aware Scheduler With Stealing Balance and Synchronized Priority in Virtualization Environments · IEEE Trans. Computers 2026
Cloud and datacenter computing › cloud security
secure container runtime
1.012026
SKernel: An Elastic and Efficient Secure Container System at Scale with a Split-Kernel Architecture · EuroSys 2026
Cloud and datacenter computing › virtualization › virtual machine management
virtual machine scheduling
1.012026
DCS3: A Dual-Layer Co-Aware Scheduler With Stealing Balance and Synchronized Priority in Virtualization Environments · IEEE Trans. Computers 2026
Cloud and datacenter computing › serverless computing
cold start mitigation
0.912025
Fork in the Road: Reflections and Optimizations for Cold Start Latency in Production Serverless Systems · OSDI 2025
Cloud and datacenter computing
serverless computing
0.912025
Fork in the Road: Reflections and Optimizations for Cold Start Latency in Production Serverless Systems · OSDI 2025
Cloud and datacenter computing › virtualization
device pass-through
0.812024
Un-IOV: Achieving Bare-Metal Level I/O Virtualization Performance for Cloud Usage With Migratability, Scalability and Transparency · IEEE Trans. Computers 2024
Cloud and datacenter computing › virtualization
i/o virtualization
0.812024
Un-IOV: Achieving Bare-Metal Level I/O Virtualization Performance for Cloud Usage With Migratability, Scalability and Transparency · IEEE Trans. Computers 2024
Cloud and datacenter computing › virtualization › virtual machine migration
live migration
0.812024
Un-IOV: Achieving Bare-Metal Level I/O Virtualization Performance for Cloud Usage With Migratability, Scalability and Transparency · IEEE Trans. Computers 2024
Cloud and datacenter computing › virtualization
paravirtualization
0.812024
Un-IOV: Achieving Bare-Metal Level I/O Virtualization Performance for Cloud Usage With Migratability, Scalability and Transparency · IEEE Trans. Computers 2024
Cloud and datacenter computing › virtualization
virtual machine migration
0.812024
Un-IOV: Achieving Bare-Metal Level I/O Virtualization Performance for Cloud Usage With Migratability, Scalability and Transparency · IEEE Trans. Computers 2024
Cloud and datacenter computing › autoscaling
container autoscaling
0.312026
SKernel: An Elastic and Efficient Secure Container System at Scale with a Split-Kernel Architecture · EuroSys 2026
Cloud and datacenter computing › cluster resource management and scheduling
cluster resource management
0.312025
Fork in the Road: Reflections and Optimizations for Cold Start Latency in Production Serverless Systems · OSDI 2025

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

split-kernel architecture · 2.0hardware virtualization · 2.0work stealing · 1.0priority synchronization · 1.0virtio accelerator · 0.8SR-IOV · 0.8
YearPublicationVenuePosition
2026 SKernel: An Elastic and Efficient Secure Container System at Scale with a Split-Kernel Architecture
abstract
Secure containers leverage hardware virtualization to isolate container sandboxes, enabling dedicated guest kernels to mitigate shared kernel attacks prevalent in traditional systems. However, existing approaches struggle with a fundamental trade-off: VM-based solutions (e.g., Kata) prioritize performance but lack elasticity and on-demand usage for volatile and bursty workloads, while lightweight methods (e.g., gVisor) rely on the host kernel for dynamic resource management at the cost of significant performance degradation due to guest-host dependencies.
Xiaohu Chai, Keyang Hu, Jianfeng Tan, Tiwei Bie, Guotao Tan, Anqi Shen, Dawei Shen, Xinyao Yang, Zhengyu He, Dong Du 0003, Yubin Xia, Kang Chen 0001, Yu Chen 0004
EuroSys4
2026 DCS3: A Dual-Layer Co-Aware Scheduler With Stealing Balance and Synchronized Priority in Virtualization Environments
abstract
Virtualization environments (e.g., containers and hypervisors) achieve isolation of multiple runtime entities but result in two mutually isolated guest and host layers. Such cross-ayer isolation could cause high latency and low throughput of the system. Previous aware scheduling and double scheduling fail to achieve bidirectional coordination between the guest and host layers. To address this challenge, we develop DCS3, a Dual-layer Co-aware Scheduler that combines stealing balance and synchronized priority. Stealing balancing migrates tasks between virtual CPU (vCPU) queues for load balance based on the workloads of physical CPUs (pCPUs). Synchronized priority dynamically adjusts the thread priorities running on the pCPUs according to the current vCPU workloads. The vCPUs and pC-PUs belong to the guest and host layers, respectively. Compared with aware scheduling, double scheduling, and DCS2 (i.e., DCS3 without synchronized priority), DCS3 has the following obvious advantages: 1) Requests Per Second (RPS) increases by up to 52%, 55%, and 2%, respectively; 2) request latency decreases by up to 72%, 71%, and 20%, respectively.
Chenglai Xiong, Guoqi Xie, Zhongjia Wang, Zhenli He, Shaowen Yao 0001, Jianfeng Tan, Tiwei Bie, Shoumeng Yan
IEEE Trans. Computers9
2025 Fork in the Road: Reflections and Optimizations for Cold Start Latency in Production Serverless Systems
Xiaohu Chai, Keyang Hu, Jianfeng Tan, Tiwei Bie, Anqi Shen, Dawei Shen, Qi Xing, Shun Song, Tongkai Yang, Zhengyu He, Dong Du 0003, Yubin Xia, Kang Chen 0001, Yu Chen 0004
OSDI5
2024 Un-IOV: Achieving Bare-Metal Level I/O Virtualization Performance for Cloud Usage With Migratability, Scalability and Transparency
abstract
I/O virtualization is utilized by cloud platforms to provide tenants with efficient, scalable, and manageable network and storage services. The de-facto industrial standard, paravirtualization, offers rich cloud functionality by introducing split front-end and back-end drivers in the guest and host operating systems, respectively. Given this fact, paravirtualization incurs host inefficiency and performance overhead. Thus, emerging hardware virtio accelerators (i.e., SRIOV-capable devices that conform to virtio specification) with device passthrough technologies mitigate the performance issue. However, adopting these devices presents the challenge of insufficient support for live migration.This paper proposes Un-IOV, a novel I/O virtualization system that simultaneously achieves bare-metal level I/O performance and migratability. The key idea is to develop a new hybrid virtualization stack with: (1) a host-bypassed direct data path for virtio accelerators, and (2) a relayed control path guaranteeing seamless live migration support. Un-IOV achieves high scalability by consuming minimum host resources. Extensive experiment results demonstrate that Un-IOV achieves superior network and storage virtualization performance than software implementations with comparable performance of direct passthrough I/O virtualization, while imposing zero guest modification (i.e., guest transparency).
Zongpu Zhang, Chenbo Xia, Cunming Liang, Jian Li 0021, Chen Yu 0003, Tiwei Bie, Roberts Martin, Dan Daly, Xiao Wang 0084, Haibing Guan
IEEE Trans. Computers6