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ASE 2022

MCDA Framework for Edge-Aware Multi-Cloud Hybrid Architecture Recommendation

Manish Ahuja, Sukhavasi Narendranath, Swapnajeet Gon Choudhury, Kaushik Amar Das, Kapil Singi, Kuntal Dey, Vikrant Kaulgud

PDFDOI 10.1145/3551349.3559501dblp

Abstract

Deploying 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.

BibTeX
@inproceedings{Ahuja-al:ASE22,
  author    = {Manish Ahuja and
               Sukhavasi Narendranath and
               Swapnajeet Gon Choudhury and
               Kaushik Amar Das and
               Kapil Singi and
               Kuntal Dey and
               Vikrant Kaulgud},
  title     = {{MCDA} Framework for {Edge-Aware} {Multi-Cloud} Hybrid Architecture Recommendation},
  booktitle = {ASE},
  pages     = {137:1--137:2},
  publisher = {{ACM}},
  year      = {2022},
}

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