MapReduce Processing with 5G networks

Abstract

MapReduce processing, which was originally designed to be executed on a cluster of high-performance servers, is also useful for processing data generated at the edge of a network. To support edge computing, we previously developed an approach to enable processing in embedded computers connected through wired or wireless local area networks in a peer-to-peer manner. Here, we extend our approach to give it with the ability to work 5G networks, which connects nodes at the edge to base stations but not directly nodes. This paper describes the extension and its performance. The extension has several contributions in common with other embedded computing systems for 5G networks.