Demo Data from VLDB 2026 / reviewers in the wild / expert
Aaron Drake
dblp:150/3290
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2015
0000-0002-7118-667XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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 networks
1 paper |
Cellular and mobile networks · 61% Network performance modeling · 30% Network measurement and analytics · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cellular and mobile networks
cellular network performance |
0.2 | 1 | 2014 | Discovering fine-grained RRC state dynamics and performance impacts in cellular networks · MobiCom 2014 |
Network performance modeling
cross-layer analysis |
0.2 | 1 | 2014 | Discovering fine-grained RRC state dynamics and performance impacts in cellular networks · MobiCom 2014 |
Cellular and mobile networks › radio resource management
radio resource control |
0.2 | 1 | 2014 | Discovering fine-grained RRC state dynamics and performance impacts in cellular networks · MobiCom 2014 |
Network measurement and analytics › mobile network measurement
cellular network measurement |
0.1 | 1 | 2014 | Discovering fine-grained RRC state dynamics and performance impacts in cellular networks · MobiCom 2014 |
Methods — techniques the papers use, named apart from their topics
measurement tool deployment · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Adaptive intra-refresh for low-delay error-resilient video coding
Haoming Chen, Chen Zhao 0002, Ming-Ting Sun, Aaron Drake |
J. Vis. Commun. Image Represent. | 4 |
| 2014 | Discovering fine-grained RRC state dynamics and performance impacts in cellular networksabstractTo conserve power while ensuring good performance on resource-constrained mobile devices, devices transition between different Radio Resource Control (RRC) states in response to network traffic and according to parameters specific to network operators. As RRC states significantly affect application power consumption and performance, it is important to understand how RRC state timers interact with network traffic patterns. In this paper, we show that the impact of RRC states on performance is significantly more complex and diverse than found in previous work. To do so, we introduce an open-source tool that allows the impact of RRC states on network and application performance to be measured in a robust and accurate manner on unmodified user devices, and deploy the tool in 23 countries around the world to test a broad range of cellular network technologies. We detect previously unknown performance problems which increase network latencies by up to several seconds and for LTE, can increase packet losses by an order of magnitude. Through an in-depth cross-layer analysis of several carriers, we examine the lower-layer causes of these problems. We determine that the highly complex state transitions of certain carriers, and in particular poor interactions between state demotions and network traffic, can lead to substantial, unexpected latencies. Sanae Rosen, Haokun Luo, Qi Alfred Chen, Z. Morley Mao, Jie Hui, Aaron Drake, Kevin Lau |
MobiCom | 6 |