Deploying Edge Computing Nodes for Large-Scale IoT: A Diversity Aware Approach
Zhiwei Zhao, Geyong Min, Weifeng Gao, Yulei Wu, Hancong Duan, Qiang Ni · IEEE Internet of Things Journal · 2018
The recent advances in microelectronics and communications have led to the development of large-scale Internet of Things (IoT) networks, where tremendous sensory data is generated and needs to be processed. To support realtime processing for large-scale IoT, deploying edge servers with storage and computational capability is a promising approach. In this paper, we carefully analyze the impacting factors and key challenges for edge node (EN) deployment. We then propose a novel three-phase deployment approach which considers both traffic diversity and the wireless diversity of IoT. The proposed work aims at providing real-time processing service for the IoT network and reducing the required number of ENs. We conducted extensive simulation experiments, the results show that compared to the existing works that overlooked the two kinds of diversities, the proposed work greatly reduces the number of ENs and improves the throughput between IoT and ENs.