Demo Data from EDBT 2026 / reviewers in the wild / expert
Vimal Mathew
dblp:37/5100
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Computer networks · 1 · 1 first-authorGraphics, 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 |
Content delivery and video streaming · 50% Internet of things and sensor networks · 50% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 77% Energy-efficient computing · 23% | |
| Artificial intelligence
1 paper |
Reinforcement learning · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Content delivery and video streaming
content delivery network |
0.1 | 1 | 2012 | Energy-aware load balancing in content delivery networks · INFOCOM 2012 |
Internet of things and sensor networks › energy efficiency › energy-efficient networking
energy-aware load balancing |
0.1 | 1 | 2012 | Energy-aware load balancing in content delivery networks · INFOCOM 2012 |
Parallel and multicore computing › load balancing
datacenter load balancing |
0.1 | 1 | 2012 | Energy-aware load balancing in content delivery networks · INFOCOM 2012 |
Machine learning › Reinforcement learning › hierarchical reinforcement learning › temporal abstraction
options |
0.1 | 1 | 2007 | Deictic Option Schemas · IJCAI 2007 |
Energy-efficient computing
power management |
0.0 | 1 | 2012 | Energy-aware load balancing in content delivery networks · INFOCOM 2012 |
Methods — techniques the papers use, named apart from their topics
online algorithm · 0.3offline optimization · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Energy-aware load balancing in content delivery networksabstractInternet-scale distributed systems such as content delivery networks (CDNs) operate hundreds of thousands of servers deployed in thousands of data center locations around the globe. Since the energy costs of operating such a large IT infrastructure are a significant fraction of the total operating costs, we argue for redesigning CDNs to incorporate energy optimizations as a first-order principle. We propose techniques to turn off CDN servers during periods of low load while seeking to balance three key design goals: maximize energy reduction, minimize the impact on client-perceived service availability (SLAs), and limit the frequency of on-off server transitions to reduce wear-and-tear and its impact on hardware reliability. We propose an optimal offline algorithm and an online algorithm to extract energy savings both at the level of local load balancing within a data center and global load balancing across data centers. We evaluate our algorithms using real production workload traces from a large commercial CDN. Our results show that it is possible to reduce the energy consumption of a CDN by 51% while ensuring a high level of availability that meets customer SLA requirements and incurring an average of one on-off transition per server per day. Further, we show that keeping even 10% of the servers as hot spares helps absorb load spikes due to global flash crowds and minimize any impact on availability SLAs. Finally, we show that redistributing load across highly proximal data centers can enhance service availability significantly, but has only a modest impact on energy savings. Vimal Mathew, Ramesh K. Sitaraman, Prashant J. Shenoy |
INFOCOM | 1 |
| 2007 | Deictic Option Schemas
Balaraman Ravindran, Andrew G. Barto, Vimal Mathew |
IJCAI | 3 |