Whitepaper on Reusable Hybrid and Multi-Cloud Analytics Service Framework

Bibliographic Details
Title: Whitepaper on Reusable Hybrid and Multi-Cloud Analytics Service Framework
Authors: von Laszewski, Gregor, Chang, Wo, Reinsch, Russell, Kotevska, Olivera, Karimi, Ali, Sattar, Abdul Rahman, Mazzaferro, Garry, Fox, Geoffrey C.
Publication Year: 2023
Collection: Computer Science
Subject Terms: Computer Science - Distributed, Parallel, and Cluster Computing
More Details: Over the last several years, the computation landscape for conducting data analytics has completely changed. While in the past, a lot of the activities have been undertaken in isolation by companies, and research institutions, today's infrastructure constitutes a wealth of services offered by a variety of providers that offer opportunities for reuse, and interactions while leveraging service collaboration, and service cooperation. This document focuses on expanding analytics services to develop a framework for reusable hybrid multi-service data analytics. It includes (a) a short technology review that explicitly targets the intersection of hybrid multi-provider analytics services, (b) a small motivation based on use cases we looked at, (c) enhancing the concepts of services to showcase how hybrid, as well as multi-provider services can be integrated and reused via the proposed framework, (d) address analytics service composition, and (e) integrate container technologies to achieve state-of-the-art analytics service deployment
Document Type: Working Paper
Access URL: http://arxiv.org/abs/2310.17013
Accession Number: edsarx.2310.17013
Database: arXiv
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