الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Fog computing aims to service users at the network edge similar to cloud services, which helps in supporting IoT applications in processing the data near to the end-user, especially for time-sensitive applications. It makes the resource allocation of application placement requests in a fog environment more necessary to satisfy the Quality of Experience (QoE) Influence Factors (IFs).
The Multi-Dimensional QoE (MD-QoE) algorithm proposed in a fog computing environment, is composed of two main phases. The first phase is to prioritize different IoT application placement requests depending on three main domains of IFs which are: Environment runtime context, application usage, and user expectations considering the Quality of Service (QoS) violation as a feedback. The second phase is to map and place the request to the appropriate fog node instance, depending on its proximity, computing capabilities, and expected response time. Experimental results indicate that the proposed algorithm significantly improves the QoE in respect of application placement time, application delay, network usage, and power consumption. Therefore, the proposed algorithm can improve the overall system performance with a slight increase of the fog control nodes power consumption.