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Vimal Mathew

dblp:37/5100 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Content delivery and video streaming
content delivery network
0.112012
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
0.112012
Energy-aware load balancing in content delivery networks · INFOCOM 2012
Parallel and multicore computing › load balancing
datacenter load balancing
0.112012
Energy-aware load balancing in content delivery networks · INFOCOM 2012
Machine learning › Reinforcement learning › hierarchical reinforcement learning › temporal abstraction
options
0.112007
Deictic Option Schemas · IJCAI 2007
Energy-efficient computing
power management
0.012012
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
YearPublicationVenuePosition
2012 Energy-aware load balancing in content delivery networks
abstract
Internet-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
INFOCOM1
2007 Deictic Option Schemas
Balaraman Ravindran, Andrew G. Barto, Vimal Mathew
IJCAI3