Analytics‐as‐a‐service in a multi‐cloud environment through semantically‐enabled hierarchical data processing

Jayaraman, Prem Prakash, Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346, Georgakopoulos, Dimitrios, Dustdar, Schahram, Thakker, Dhavalkumar and Ranjan, Rajiv 2017. Analytics‐as‐a‐service in a multi‐cloud environment through semantically‐enabled hierarchical data processing. Software: Practice and Experience 47 (8) , pp. 1139-1156. 10.1002/spe.2432

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Abstract

A large number of cloud middleware platforms and tools are deployed to support a variety of internet‐of‐things (IoT) data analytics tasks. It is a common practice that such cloud platforms are only used by its owners to achieve their primary and predefined objectives, where raw and processed data are only consumed by them. However, allowing third parties to access processed data to achieve their own objectives significantly increases integration and cooperation and can also lead to innovative use of the data. Multi‐cloud, privacy‐aware environments facilitate such data access, allowing different parties to share processed data to reduce computation resource consumption collectively. However, there are interoperability issues in such environments that involve heterogeneous data and analytics‐as‐a‐service providers. There is a lack of both architectural blueprints that can support such diverse, multi‐cloud environments and corresponding empirical studies that show feasibility of such architectures. In this paper, we have outlined an innovative hierarchical data‐processing architecture that utilises semantics at all the levels of IoT stack in multi‐cloud environments. We demonstrate the feasibility of such architecture by building a system based on this architecture using OpenIoT as a middleware, and Google Cloud and Microsoft Azure as cloud environments. The evaluation shows that the system is scalable and has no significant limitations or overheads. Copyright © 2016 John Wiley & Sons, Ltd.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Publisher:	Wiley
ISSN:	0038-0644
Date of First Compliant Deposit:	11 August 2020
Date of Acceptance:	3 July 2016
Last Modified:	07 Nov 2022 10:58
URI:	https://orca.cardiff.ac.uk/id/eprint/134086

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