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Nikhil Kasinadhuni

dblp:32/2413 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

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

Computer networks · 2

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
Datacenter networks · 64% Routing and switching · 36%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
Cloud and datacenter computing · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing › virtualization
network virtualization
0.312018
Andromeda: Performance, Isolation, and Velocity at Scale in Cloud Network Virtualization · NSDI 2018
Routing and switching
traffic engineering
0.212015
BwE: Flexible, Hierarchical Bandwidth Allocation for WAN Distributed Computing · SIGCOMM 2015
Cloud and datacenter computing
cluster resource management and scheduling
0.212015
BwE: Flexible, Hierarchical Bandwidth Allocation for WAN Distributed Computing · SIGCOMM 2015

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

primal-dual method · 0.4integer programming · 0.4
YearPublicationVenuePosition
2018 Andromeda: Performance, Isolation, and Velocity at Scale in Cloud Network Virtualization
Michael Dalton, David Schultz, Jacob Adriaens, Ahsan Arefin, Anshuman Gupta, Brian Fahs, Dima Rubinstein, Enrique Cauich Zermeno, Erik Rubow, James Alexander Docauer, Jesse Alpert, Jing Ai, Jon Olson, Kevin DeCabooter, Marc de Kruijf, Nan Hua, Nathan Lewis, Nikhil Kasinadhuni, Riccardo Crepaldi, Srinivas Krishnan, Subbaiah Venkata, Yossi Richter, Uday Naik, Amin Vahdat
NSDI18
2015 BwE: Flexible, Hierarchical Bandwidth Allocation for WAN Distributed Computing
abstract
WAN bandwidth remains a constrained resource that is economically infeasible to substantially overprovision. Hence, it is important to allocate capacity according to service priority and based on the incremental value of additional allocation. For example, it may be the highest priority for one service to receive 10Gb/s of bandwidth but upon reaching such an allocation, incremental priority may drop sharply favoring allocation to other services. Motivated by the observation that individual flows with fixed priority may not be the ideal basis for bandwidth allocation, we present the design and implementation of Bandwidth Enforcer (BwE), a global, hierarchical bandwidth allocation infrastructure. BwE supports: i) service-level bandwidth allocation following prioritized bandwidth functions where a service can represent an arbitrary collection of flows, ii)independent allocation and delegation policies according to user-defined hierarchy, all accounting for a global view of bandwidth and failure conditions, iii) multi-path forwarding common in traffic-engineered networks, and iv) a central administrative point to override (perhaps faulty) policy during exceptional conditions. BwE has delivered more service efficient bandwidth utilization and simpler management in production for multiple years.
Sushant Jain, Uday Naik, Anand Raghuraman, Nikhil Kasinadhuni, Enrique Cauich Zermeno, C. Stephen Gunn, Jing Ai, Björn Carlin, Mihai Amarandei-Stavila, Mathieu Robin, Aspi Siganporia, Stephen Stuart, Amin Vahdat
SIGCOMM5