Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/16481
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dc.contributor.authorNatesha B.V.
dc.contributor.authorGuddeti R.M.R.
dc.date.accessioned2021-05-05T10:30:36Z-
dc.date.available2021-05-05T10:30:36Z-
dc.date.issued2021
dc.identifier.citationJournal of Network and Computer Applications , Vol. 178 , , p. -en_US
dc.identifier.urihttps://doi.org/10.1016/j.jnca.2020.102972
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/16481-
dc.description.abstractFog computing is an emerging computation technology for handling and processing the data from IoT devices. The devices such as the router, smart gateways, or micro-data centers are used as the fog nodes to host and service the IoT applications. However, the primary challenge in fog computing is to find the suitable nodes to deploy and run the IoT application services as these devices are geographically distributed and have limited computational resources. In this paper, we design the two-level resource provisioning fog framework using docker and containers and formulate the service placement problem in fog computing environment as a multi-objective optimization problem for minimizing the service time, cost, energy consumption and thus ensuring the QoS of IoT applications. We solved the said multi-objective problem using the Elitism-based Genetic Algorithm (EGA). The proposed approach is evaluated on fog computing testbed developed using docker and containers on 1.4 GHz 64-bit quad-core processor devices. The experimental results demonstrate that the proposed method outperforms other state-of-the-art service placement strategies considered for performance evaluation in terms of service cost, energy consumption, and service time. © 2021 Elsevier Ltden_US
dc.titleAdopting elitism-based Genetic Algorithm for minimizing multi-objective problems of IoT service placement in fog computing environmenten_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

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