CCoDaMiC: a framework for coherent coordination of data migration and computation platforms
CCoDaMiC: a framework for coherent coordination of data migration and computation platforms
The amount of data generated by millions of connected IoT sensors and devices is growing exponentially. The need to extract relevant information from this data in modern and future generation computing system, necessitates efficient data handling and processing platforms that can migrate such big data from one location to other locations seamlessly and securely, and can provide a way to preprocess and analyze that data before migrating to the final destination. Various data pipeline architectures have been proposed allowing the data administrator/user to handle the data migration operation efficiently. However, the modern data pipeline architectures do not offer built-in functionalities for ensuring data veracity, which includes data accuracy, trustworthiness and security. Furthermore, allowing the intermediate data to be processed, especially in the serverless computing environment, is becoming a cumbersome task. In order to fill this research gap, this paper introduces an efficient and novel data pipeline architecture, named as CCoDaMiC (Coherent Coordination of Data Migration and Computation), which brings both the data migration operation and its computation together into one place. This also ensures that the data delivered to the next destination/pipeline block is accurate and secure. The proposed framework is implemented in private OpenStack environment and Apache Nifi.
Dehury, Chinmaya Kumar
70fd2764-04aa-4cd0-bc58-b74c66243efd
Srirama, Satish Narayana
9c7b33c8-ee2b-45f1-81eb-3d603b8be475
Chhetri, Tek Raj
c3431de5-4860-43e5-b09f-3dbb752c8490
21 March 2020
Dehury, Chinmaya Kumar
70fd2764-04aa-4cd0-bc58-b74c66243efd
Srirama, Satish Narayana
9c7b33c8-ee2b-45f1-81eb-3d603b8be475
Chhetri, Tek Raj
c3431de5-4860-43e5-b09f-3dbb752c8490
Dehury, Chinmaya Kumar, Srirama, Satish Narayana and Chhetri, Tek Raj
(2020)
CCoDaMiC: a framework for coherent coordination of data migration and computation platforms.
Future Generation Computer Systems, 109.
(doi:10.1016/j.future.2020.03.029).
Abstract
The amount of data generated by millions of connected IoT sensors and devices is growing exponentially. The need to extract relevant information from this data in modern and future generation computing system, necessitates efficient data handling and processing platforms that can migrate such big data from one location to other locations seamlessly and securely, and can provide a way to preprocess and analyze that data before migrating to the final destination. Various data pipeline architectures have been proposed allowing the data administrator/user to handle the data migration operation efficiently. However, the modern data pipeline architectures do not offer built-in functionalities for ensuring data veracity, which includes data accuracy, trustworthiness and security. Furthermore, allowing the intermediate data to be processed, especially in the serverless computing environment, is becoming a cumbersome task. In order to fill this research gap, this paper introduces an efficient and novel data pipeline architecture, named as CCoDaMiC (Coherent Coordination of Data Migration and Computation), which brings both the data migration operation and its computation together into one place. This also ensures that the data delivered to the next destination/pipeline block is accurate and secure. The proposed framework is implemented in private OpenStack environment and Apache Nifi.
Text
1-s2.0-S0167739X19330924-main
- Version of Record
More information
Accepted/In Press date: 10 March 2020
e-pub ahead of print date: 18 March 2020
Published date: 21 March 2020
Identifiers
Local EPrints ID: 481468
URI: http://eprints.soton.ac.uk/id/eprint/481468
ISSN: 0167-739X
PURE UUID: 5ef52e3f-0ddb-4522-8ce7-4c93590cde27
Catalogue record
Date deposited: 29 Aug 2023 17:09
Last modified: 17 Mar 2024 04:21
Export record
Altmetrics
Contributors
Author:
Chinmaya Kumar Dehury
Author:
Satish Narayana Srirama
Author:
Tek Raj Chhetri
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics