Demo Data from VLDB 2026 / reviewers in the wild / expert
Zelin Lin
dblp:331/4358
· DBLP profile ↗
3ranked-venue papers
0as first author
3since 2021 · last 2025
0009-0005-7308-9450ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 2 since 2021Computer networks · 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 networks
2 papers |
Edge and fog computing · 65% Software-defined and programmable networks · 23% Cellular and mobile networks · 12% | |
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Cloud and datacenter computing · 100% |
Topics — the 8 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Edge and fog computing › edge devices
heterogeneous edge devices |
0.9 | 1 | 2025 | Efficient Service Function Chain Placement Over Heterogeneous Devices in Deviceless Edge Computing Environments · IEEE Trans. Computers 2025 |
Edge and fog computing
resource management |
0.9 | 1 | 2025 | Efficient Service Function Chain Placement Over Heterogeneous Devices in Deviceless Edge Computing Environments · IEEE Trans. Computers 2025 |
Software-defined and programmable networks › network function virtualization
service function chain deployment |
0.9 | 1 | 2025 | Efficient Service Function Chain Placement Over Heterogeneous Devices in Deviceless Edge Computing Environments · IEEE Trans. Computers 2025 |
Cloud and datacenter computing › virtualization
lightweight virtualization |
0.9 | 1 | 2025 | Efficient Service Function Chain Placement Over Heterogeneous Devices in Deviceless Edge Computing Environments · IEEE Trans. Computers 2025 |
Cloud and datacenter computing
virtualization |
0.9 | 1 | 2025 | Efficient Service Function Chain Placement Over Heterogeneous Devices in Deviceless Edge Computing Environments · IEEE Trans. Computers 2025 |
Cloud and datacenter computing
serverless computing |
0.8 | 1 | 2024 | Mobility-Aware Seamless Virtual Function Migration in Deviceless Edge Computing Environments · IEEE Trans. Mob. Comput. 2024 |
Cellular and mobile networks
mobility management |
0.2 | 1 | 2024 | Mobility-Aware Seamless Virtual Function Migration in Deviceless Edge Computing Environments · IEEE Trans. Mob. Comput. 2024 |
Cellular and mobile networks › mobility management
user mobility |
0.2 | 1 | 2024 | Mobility-Aware Seamless Virtual Function Migration in Deviceless Edge Computing Environments · IEEE Trans. Mob. Comput. 2024 |
Methods — techniques the papers use, named apart from their topics
quasi-convex optimization · 1.7receding horizon control · 1.5integer linear programming · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Efficient Service Function Chain Placement Over Heterogeneous Devices in Deviceless Edge Computing EnvironmentsabstractHeterogeneous devices in edge computing bring challenges as well as opportunities for edge computing to utilize powerful and heterogeneous hardware for a variety of complex tasks. In this paper, we propose a service function chain placement strategy considering the heterogeneity of devices in deviceless edge computing environments. The service function chain system utilizes lightweight virtualization technologies to manage resources, considering the heterogeneity of devices to support various complex tasks, and offer low latency services to user requests. We propose an optimal service function chain placement problem minimizing the service delay and formulate it into a quasi-convex problem. We implement different edge applications that can be served by function chains and conduct extensive experiments over real heterogeneous edge devices. Results from the experiments and simulations show that our proposed service function chain scheme is applicable in edge environments, and perform well over services latency, resource utilization as well as the power consumption of edge devices. Yaodong Huang, Zelin Lin, Xiaojun Shang, Yukun Yuan 0001, Laizhong Cui, Yuanyuan Yang 0001 |
IEEE Trans. Computers | 3 |
| 2024 | Mobility-Aware Seamless Virtual Function Migration in Deviceless Edge Computing EnvironmentsabstractServerless Computing and Function-as-a-Service (FaaS) offer convenient and transparent services to developers and users. The deployment and resource allocation of services are managed by the cloud service providers. Meanwhile, the development of smart mobile devices and network technology enables the collection and transmission of a huge amount of data, which shifts tasks to the network edge for mobile users. In this paper, we propose a deviceless edge computing system targeting the mobility of end users using the data migration of virtual functions. We focus on the adjustment of migration among virtual functions to provide uninterrupted services to mobile users. We introduce the deviceless edge computing model and propose a seamless data migration scheme of virtual functions with limited involvement of function developers. We formulate the migration decision problem into integer linear programming and use receding horizon control (RHC) for online solutions. We implement the migration system to support delay-sensitive scenarios over real edge devices and develop a streaming game as the virtual function to test the performance. Extensive experiments in real scenarios exhibit the system has the ability to support high-mobility and delay-sensitive application scenarios. Extensive simulation results show the applicability of the proposed system over large-scale networks. Yaodong Huang, Zelin Lin, Changkang Mo, Xiaojun Shang, Laizhong Cui, Yuanyuan Yang 0001 |
IEEE Trans. Mob. Comput. | 2 |
| 2022 | Mobility-aware Seamless Virtual Function Migration in Deviceless Edge Computing EnvironmentsabstractServerless Computing and Function-as-a-Service (FaaS) offer convenient and transparent services to developers and users. The deployment and resource allocation of services are managed by the cloud service providers. Meanwhile, the development of smart mobile devices and network technology enables the collection and transmission of a huge amount of data, which creates the mobile edge computing shifting tasks to the network edge for mobile users. In this paper, we propose a deviceless edge computing system targeting the mobility of end users. We focus on the migration of virtual functions to provide uninterrupted services to mobile users. We introduce the deviceless edge computing model and propose a seamless migration scheme of virtual functions with limited involvement of function developers. We formulate the migration decision problem into integer linear programming and use receding horizon control (RHC) for online solutions. We implement the migration system and algorithm to support delay-sensitive scenarios over real edge devices and develop a streaming game as the virtual function to test the performance. Extensive experiments in real scenarios exhibit the system has the ability to support high-mobility and delay-sensitive application scenarios. Extensive simulation results also show its applicability over large-scale networks. Yaodong Huang, Zelin Lin, Xiaojun Shang, Laizhong Cui, Joshua Zhexue Huang |
ICDCS | 2 |