Demo Data from SIGIR 2026 / reviewers in the wild / expert
Zhichao Mo
dblp:153/6008
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Graphics, computer vision, multimedia, augmented reality and games · 1
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 |
Content delivery and video streaming · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cloud and datacenter computing › datacenter network
datacenter traffic |
0.3 | 1 | 2017 | Cluster-Aware Virtual Machine Collaborative Migration in Media Cloud · IEEE Trans. Parallel Distributed Syst. 2017 |
Cloud and datacenter computing › virtualization › virtual machine management › virtual machine placement
traffic-aware VM placement |
0.3 | 1 | 2017 | Cluster-Aware Virtual Machine Collaborative Migration in Media Cloud · IEEE Trans. Parallel Distributed Syst. 2017 |
Cloud and datacenter computing › virtualization
virtual machine migration |
0.3 | 1 | 2017 | Cluster-Aware Virtual Machine Collaborative Migration in Media Cloud · IEEE Trans. Parallel Distributed Syst. 2017 |
Methods — techniques the papers use, named apart from their topics
clustering algorithm · 0.6placement algorithms · 0.3placement algorithm · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Cluster-Aware Virtual Machine Collaborative Migration in Media CloudabstractMedia cloud has become a promising paradigm for deploying large-scale streaming media applications at a reduced cost. Due to dynamic and diverse demands of users, media cloud presents two crucial characteristics: high resource consumption and dynamic traffic among media servers. Consequently, Virtual Machine (VM) migration in media cloud is highly required to suit varying resource requirements and the dynamic traffic patterns. Moreover, migration of such bandwidth-intensive media applications in media cloud needs cautious handling, especially for the internal traffic of Data Center Networks (DCN). However, existing media cloud resource management schemes or traffic-aware VM deployment approaches are insufficient for media cloud, ignoring the characteristics of either cloud infrastructure or media streaming requirements. In this paper, we propose a cluster-aware VM collaborative migration scheme for media cloud, tightly integrating clustering, placement, and dynamic migration process. The scheme employs a clustering algorithm and a placement algorithm to obtain ideal migration strategies for newly perceived media server clusters, and a migration algorithm to effectively accomplish the migration process of media servers. Evaluation results demonstrate that our scheme can effectively migrate virtual media servers in media cloud, while reducing the total internal traffic in DCN under the resource consumption constraints of media streaming applications. Weizhan Zhang, Zhichao Mo, Zongqing Lu 0002 |
IEEE Trans. Parallel Distributed Syst. | 4 |
| 2014 | CBC: Caching for cloud-based VOD systems
Weizhan Zhang, Zhichao Mo |
Multim. Tools Appl. | 2 |