Petri, Ioan ORCID: https://orcid.org/0000-0002-1625-8247, Diaz-Montes, Javier, Zou, Mengsong, Zamani, Ali Reza, Beach, Thomas ORCID: https://orcid.org/0000-0001-5610-8027, Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646, Parashar, Manish and Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400 2016. Distributed multi-cloud based building data analytics. Developing Interoperable and Federated Cloud Architecture, pp. 143-170. (10.4018/978-1-5225-0153-4.ch006) |
Abstract
Cloud computing has emerged as attractive platform for computing data intensive applications. However, efficient computation of this kind of workloads requires understanding how to store, process, and analyse large volumes of data in a timely manner. Many “smart cities” applications, for instance, identify how data from building sensors can be combined together to support applications such as emergency response, energy management, etc. Enabling sensor data to be transmitted to a cloud environment for processing provides a number of benefits, such as scalability and on-demand provisioning of computational resources. In this chapter, we propose the use of a multi-layer cloud infrastructure that distributes processing over sensing nodes, multiple intermediate/gateways nodes, and large data centres. Our solution aims at utilising the pervasive computational capabilities located at the edge of the infrastructure and along the data path to reduce data movement to large data centres located “deep” into the infrastructure and perform a more efficient use of computing and network resources.
Item Type: | Book Section |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering Computer Science & Informatics |
ISBN: | 9781522501541 |
ISSN: | 2327-3453 |
Last Modified: | 01 Nov 2022 11:11 |
URI: | https://orca.cardiff.ac.uk/id/eprint/94106 |
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