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Fog computing is an extension of cloud computing right to the edge of the network, and seeks to minimize service latency and average response time in applications, thereby enhancing the end-user experience. However, there still is the need to define where the service should run for attaining maximum efficiency. By way of the work proposed in this paper, we seek to develop a resource-aware placement of data analytics platform in fog computing architecture, that would adaptively deploy the analytic platform to run either on the cloud, or the fog, thus reducing the network costs and response time for the user.
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Procedia Computer Science
Waterford Institute of Technology
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