Demo Data from EDBT 2026 / reviewers in the wild / expert
Hengjing He
dblp:204/0597
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0002-1448-5585ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author
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 |
Cloud and datacenter computing · 100% | |
| Computer networks
1 paper |
Internet of things and sensor networks · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cloud and datacenter computing
cloud architecture |
0.4 | 1 | 2020 | Research on the Architecture and its Implementation for Instrumentation and Measurement Cloud · IEEE Trans. Serv. Comput. 2020 |
Cloud and datacenter computing › virtualization
resource virtualization |
0.4 | 1 | 2020 | Research on the Architecture and its Implementation for Instrumentation and Measurement Cloud · IEEE Trans. Serv. Comput. 2020 |
Internet of things and sensor networks › wireless sensor network
sensor management |
0.1 | 1 | 2020 | Research on the Architecture and its Implementation for Instrumentation and Measurement Cloud · IEEE Trans. Serv. Comput. 2020 |
Methods — techniques the papers use, named apart from their topics
service wrapping · 0.9resource virtualization · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Research on the Architecture and its Implementation for Instrumentation and Measurement CloudabstractCloud computing has brought a new method of resource utilization and management. Nowadays some researchers are working on cloud-based instrumentation and measurement systems designated as Instrumentation and Measurement Clouds (IMCs). However, until now, no standard definition or detailed architecture with an implemented system for IMC has been presented. This paper adopts the philosophy of cloud computing and brings forward a relatively standard definition and a novel architecture for IMC. The architecture inherits many key features of cloud computing, such as service provision on demand, scalability and so on, for remote Instrumentation and Measurement (IM) resource utilization and management. In the architecture, instruments and sensors are virtualized into abstracted resources, and commonly used IM functions are wrapped into services. Users can use these resources and services on demand remotely. Platforms implemented under such architecture can reduce the investment for building IM systems greatly, enable remote sharing of IM resources, increase utilization efficiency of various resources, and facilitate processing and analyzing of Big Data from instruments and sensors. Practical systems with a typical application are implemented upon the architecture. Results demonstrate that the novel IMC architecture can provide a new effective and efficient framework for establishing IM systems. Hengjing He, Wei Zhao 0031, Songling Huang, Geoffrey C. Fox, Qing Wang 0014 |
IEEE Trans. Serv. Comput. | 1 |