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MeFILL: A Multi-edged Framework for Intelligent and Low Latency Mobile IoT Services

With the development of the cellular network in the last decade, the number of IoT devices is growing exponentially and IoT applications are becoming more complex with higher requirements for Key Performance Indicators (KPIs) such as latency, accuracy and energy consumption. To address these challenges, the edge computing paradigm is often adopted to push the computing capabilities to the edge servers nearest to end-users. However, the Quality of Experience (QoE) of IoT applications is still hard to guarantee because the nearest edge servers change while users roam around. In this paper, we propose MeFILL, a Multi-edged Framework for Intelligent and Low Latency mobile IoT applications, which reduces the latencies and improves the reliability with the seamless handover of IoT devices between edge servers and leverages the Distributed Deep Learning (DDL) collaboration among edge servers. The comparison experiments show that MeFILL can effectively optimize performance KPIs of mobile IoT applications.