Abstract:
Edge computing is an emerging computing paradigm where data is generated and processed in the field using distributed computing devices. Many applications such as real-time video processing, augmented/virtual reality gaming, environment sensing, benefit from such decentralized, close-to-user deployments where low-latency, real-time results are expected. As with any distributed application, one of the key challenges in the development of collaborative applications is how to efficiently share data and state among multiple edge clients. The dynamic and heterogeneous environment together with diverse application’s requirements make data sharing at the edge a challenging problem. Although there have been prior efforts, a systematic understanding of the area is missing. In this paper, we conduct a methodological study of different edge applications, their data sharing needs, and designs of state-of-the-art systems. In the process, we identify design options, under-explored opportunities, and associated challenges. We then present Griffin, our edge data sharing service, and seek feedback on its design.
