Ramaswamy Aditya

dblp:271/5953 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 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
Network management and operations · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
datacenter operations
0.412020
Scouts: Improving the Diagnosis Process Through Domain-customized Incident Routing · SIGCOMM 2020
Network management and operations › fault management
fault diagnosis
0.112020
Scouts: Improving the Diagnosis Process Through Domain-customized Incident Routing · SIGCOMM 2020

Methods — techniques the papers use, named apart from their topics

machine learning · 0.9
YearPublicationVenuePosition
2020 Scouts: Improving the Diagnosis Process Through Domain-customized Incident Routing
abstract
Incident routing is critical for maintaining service level objectives in the cloud: the time-to-diagnosis can increase by 10x due to mis-routings. Properly routing incidents is challenging because of the complexity of today's data center (DC) applications and their dependencies. For instance, an application running on a VM might rely on a functioning host-server, remote-storage service, and virtual and physical network components. It is hard for any one team, rule-based system, or even machine learning solution to fully learn the complexity and solve the incident routing problem. We propose a different approach using per-team Scouts. Each teams' Scout acts as its gate-keeper --- it routes relevant incidents to the team and routes-away unrelated ones. We solve the problem through a collection of these Scouts. Our PhyNet Scout alone --- currently deployed in production --- reduces the time-to-mitigation of 65% of mis-routed incidents in our dataset.
Nofel Yaseen, Robert MacDavid, Felipe Vieira Frujeri, Vincent Liu 0001, Ricardo Bianchini, Ramaswamy Aditya, Xiaohang Wang 0008, Henry Lee, David A. Maltz, Minlan Yu, Behnaz Arzani
SIGCOMM7