Demo Data from EDBT 2026 / reviewers in the wild / expert
Swapnajeet Gon Choudhury
dblp:276/3598
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021
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 |
Edge and fog computing · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Edge and fog computing › edge-cloud computing
edge-cloud deployment |
0.6 | 1 | 2022 | MCDA Framework for Edge-Aware Multi-Cloud Hybrid Architecture Recommendation · ASE 2022 |
Cloud and datacenter computing › cloud deployment
hybrid cloud |
0.6 | 1 | 2022 | MCDA Framework for Edge-Aware Multi-Cloud Hybrid Architecture Recommendation · ASE 2022 |
Cloud and datacenter computing › cloud deployment
multi-cloud |
0.6 | 1 | 2022 | MCDA Framework for Edge-Aware Multi-Cloud Hybrid Architecture Recommendation · ASE 2022 |
Cloud and datacenter computing › cluster resource management and scheduling › resource scheduling
application placement |
0.2 | 1 | 2022 | MCDA Framework for Edge-Aware Multi-Cloud Hybrid Architecture Recommendation · ASE 2022 |
Cloud and datacenter computing
resource management |
0.2 | 1 | 2022 | MCDA Framework for Edge-Aware Multi-Cloud Hybrid Architecture Recommendation · ASE 2022 |
Methods — techniques the papers use, named apart from their topics
multicriteria decision analysis · 0.6multi-criteria decision analysis · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | MCDA Framework for Edge-Aware Multi-Cloud Hybrid Architecture RecommendationabstractDeploying applications on hybrid clouds with computational artifacts distributed over public backends and private edges involve several constraints. Designing such deployment requires application architects to solve several challenges, spanning over hard regulatory policy constraints as well as business policy constraints such as enablement of privacy by on-prem processing of data to the extent the business wants, backend support of privacy enabling technologies (PET), sustainability in terms of green energy utilization, latency sensitivity of the application. In this paper, we propose to optimize hybrid cloud application architectures, while taking all those factors into consideration, and empirically demonstrate the effectiveness of our approach. To the best of our knowledge, this work is the first of its kind. Manish Ahuja, Sukhavasi Narendranath, Swapnajeet Gon Choudhury, Kaushik Amar Das, Kapil Singi, Kuntal Dey, Vikrant S. Kaulgud |
ASE | 3 |