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dc.contributor.authorMartin J.P.
dc.contributor.authorKandasamy A.
dc.contributor.authorChandrasekaran K.
dc.date.accessioned2021-05-05T10:27:35Z-
dc.date.available2021-05-05T10:27:35Z-
dc.date.issued2020
dc.identifier.citationJournal of Ambient Intelligence and Humanized Computing Vol. 11 , 11 , p. 5259 - 5278en_US
dc.identifier.urihttps://doi.org/10.1007/s12652-020-01854-x
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/15645-
dc.description.abstractThe fog computing paradigm has emanated as a widespread computing technology to support the execution of the internet of things applications. The paradigm introduces a distributed, hierarchical layer of nodes collaboratively working together as the Fog layer. User devices connected to Fog nodes are often non-stationary. The location-aware attribute of Fog computing, deems it necessary to provide uninterrupted services to the users, irrespective of their locations. Migration of user application modules among the Fog nodes is an efficient solution to tackle this issue. In this paper, an autonomic framework MAMF, is proposed to perform migrations of containers running user modules, while satisfying the Quality of Service requirements. The hybrid framework employing MAPE loop concepts and Genetic Algorithm, addresses the migration of containers in the Fog environment, while ensuring application delivery deadlines. The approach uses the pre-determined value of user location for the next time instant, to initiate the migration process. The framework was modelled and evaluated in iFogSim toolkit. The re-allocation problem was also mathematically modelled as an Integer Linear Programming problem. Experimental results indicate that the approach offers an improvement in terms of network usage, execution cost and request execution delay, over the existing approaches. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.en_US
dc.titleMobility aware autonomic approach for the migration of application modules in fog computing environmenten_US
dc.typeArticleen_US
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