VINUEZA NARANJO, Paola G.    PATIL, Navinkumar J. A Fog Assisted Cloud Paradigm for accessibility and collaboration to Genomic Data Analysis Fog Asiste Cloud. []. , 1, 2, pp.70-82.   01--2021. ISSN 2631-2654.  https://doi.org/10.37135/unach.ns.001.02.08.

Increasingly growing Next-generation sequencing requires large-scale computing resources to handle the huge amount of data produced. The Cloud computing paradigm readily handles huge data but the core issue with this paradigm is transfer of enormous data to and from cloud computers due to limited bandwidth which lies in the centralized nature of a Cloud computing architecture that is located far away from users. An architecture where computing power is distributed more evenly throughout the network is the way to combat this problem. The architecture should drive the processing capacity towards the edge of the network, closer to the source of the data. For this propose Fog computing offers a promising solution to move computational capabilities closer to the data generated and will be the solution to gain traction in genomics research. We propose a novel Collaborative-Fog (Co-Fog) model that adopts the Fog and Cloud computing paradigms to manage huge genomic data sets and to enable understanding of how key stakeholders can manage the interaction and collaboration. The present work describes the Co-Fog model that promises increased performance, energy efficiency, reduced latency, faster response time, scalability, and better localized accuracy for future large-scale collaborations in genomics.

: Big data; Distributed resource management; Cloud computing; Fog computing; Next-generation sequencing (NGS).

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