With improvements in computation and storage resources, data access through the network becomes the bottleneck for several cloud applications. Even with high-speed networks, the high latency of the cloud access makes it unfeasible or unfavourable for latency-sensitive applications such as autonomous driving, smart factories, and video streaming. Edge computing provides a solution by utilizing the network edge resources that are closer to the end users. Nevertheless, it is a non-trivial task to design a large-scale edge-capable system that is stable, fault-tolerant, and efficient.
In this paper, present the design of EdgeKV: a novel general-purpose distributed key-value store for the network edge. We demonstrate the features of EdgeKV for achieving high efficiency and scalability while providing flexibility, ease of use, and data privacy. We evaluated our prototype on the Grid'5000 framework with multiple realistic Yahoo! Cloud Serving Benchmark (YCSB) workloads. Our initial results show that EdgeKV achieves 72% higher throughput and 47% lower latency on average than centralized cloud storage, for read-dominated workloads.