A Fast Hybrid Data Sharing Framework for Hierarchical Mobile Edge Computing

Edge computing satisfies the stringent latency requirements of data access and processing for applications running on edge devices. The data location service is a key function to provide data storage and retrieval to enable these applications. However, it still lacks research of a scalable and low-latency data location service in mobile edge computing. Meanwhile, the existing solutions, such as DNS and DHT, fail to meet the low latency requirement of mobile edge computing. This paper presents a low-latency hybrid data-sharing framework, HDS, in which the data location service is divided into two parts: intra-region and inter-region. In the intra-region part, we design a data sharing protocol called Cuckoo Summary to achieve fast data localization. In the inter-region part, we develop a geographic routing based scheme to achieve efficient data localization with only one overlay hop. The advantages of HDS include short response latency, low implementation overhead, and few false positives. We implement our HDS framework based on a P4 prototype. The experimental results show that, compared to the state-of-the-art solutions, our design achieves 50.21% shorter lookup paths and 92.75% fewer false positives.