Demo Data from VLDB 2026 / reviewers in the wild / expert
M. Y. Y. Leung
dblp:90/6182
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2002
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2 · 2 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 networks
2 papers |
Content delivery and video streaming · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Performance modeling and evaluation · 56% Storage systems · 44% | |
| Computer graphics and multimedia
1 paper |
Multimedia systems and quality of experience · 100% |
Topics — the 4 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Content delivery and video streaming › video-on-demand
interactive video-on-demand |
0.0 | 1 | 2002 | Use of Analytical Performance Models for System Sizing and Resource Allocation in Interactive Video-on-Demand Systems Employing Data Sharing Techniques · IEEE Trans. Knowl. Data Eng. 2002 |
Content delivery and video streaming
video-on-demand |
0.0 | 1 | 2002 | Use of Analytical Performance Models for System Sizing and Resource Allocation in Interactive Video-on-Demand Systems Employing Data Sharing Techniques · IEEE Trans. Knowl. Data Eng. 2002 |
Performance modeling and evaluation
analytical modeling |
0.0 | 1 | 2002 | Use of Analytical Performance Models for System Sizing and Resource Allocation in Interactive Video-on-Demand Systems Employing Data Sharing Techniques · IEEE Trans. Knowl. Data Eng. 2002 |
Multimedia systems and quality of experience › video streaming
video-on-demand |
0.0 | 1 | 1997 | Buffer and I/O Resource Pre-allocation for Implementing Batching and Buffering Techniques for Video-on-Demand Systems · ICDE 1997 |
Methods — techniques the papers use, named apart from their topics
queueing analysis · 0.1analytical modeling · 0.1resource pre-allocation · 0.1piggybacking · 0.1buffering · 0.1batching · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | Use of Analytical Performance Models for System Sizing and Resource Allocation in Interactive Video-on-Demand Systems Employing Data Sharing TechniquesabstractIn designing cost-effective video-on-demand (VOD) servers, efficient resource management and proper system sizing are of great importance. In addition to large storage and I/O bandwidth requirements, support of interactive VCR functionality imposes additional resource requirements on the VOD system in terms of storage space, as well as disk and network bandwidth. Previous works have used data sharing techniques (such as batching, buffering, and adaptive piggybacking) to reduce the I/O demand on the storage server. However, such data sharing techniques complicate the provision of VCR functions and diminish the amount of benefit that can be obtained from data sharing techniques. The main contribution of this paper is a simple, yet powerful, analytical modeling approach which allows for analysis, system sizing, resource allocation, and parameter setting for a fairly general class of data sharing techniques which are used in conjunction with the providing of VCR-type functionality. Using this mathematical model, we can determine the proper amount of resources to be allocated for normal playback as well as for service of VCR functionality requests while satisfying predefined system performance requirements. To illustrate the usefulness of our model, we focus on a specific data sharing scheme which combines the use of batching, buffering, and adaptive piggybacking, as well as allows for the use of VCR functions. We show how to utilize this mathematical model for system sizing and resource allocation purposes. M. Y. Y. Leung, John C. S. Lui, Leana Golubchik |
IEEE Trans. Knowl. Data Eng. | 1 |
| 1997 | Buffer and I/O Resource Pre-allocation for Implementing Batching and Buffering Techniques for Video-on-Demand SystemsabstractTo design a cost effective VOD server, it is important to carefully manage the system resources so that the number of concurrent viewers can be maximized. Previous research results use data sharing techniques, such as batching, buffering, and piggybacking, to reduce the demand for I/O resources In a VOD system. However, these techniques still suffer from the problem that additional I/O resources are needed in the system for providing VCR functionality-without careful resource management, the benefits of these data sharing techniques can be lost. In this paper, we first introduce a model for determining the amount of resources required for supporting both normal playback and VCR functionality to satisfy predefined performance characteristics. Consequently, this model allows us to maximize the benefits of data sharing techniques. Furthermore, one important application of this model is its use in making system sizing decisions. Proper system sizing will result in a more cost-effective VOD system. M. Y. Y. Leung, John C. S. Lui, Leana Golubchik |
ICDE | 1 |