EdgeSphere: A Three-Tier Architecture for Cognitive Edge Computing

TL;DR

EdgeSphere introduces a three-tier architecture for cognitive edge computing that enables in situ data analysis across cloud, gateways, and devices, optimizing resource use with Apache Mesos.

Contribution

The paper presents a novel three-tier architecture, EdgeSphere, for efficient resource management and data analysis at the edge, addressing challenges of heterogeneity and connectivity.

Findings

Effective resource scheduling with Apache Mesos

Successful deployment in practical scenarios

Enhanced in situ data processing capabilities

Abstract

Computing at the edge is increasingly important as Internet of Things (IoT) devices at the edge generate massive amounts of data and pose challenges in transporting all that data to the Cloud where they can be analyzed. On the other hand, harnessing the edge data is essential for offering cognitive applications, if the challenges, such as device capabilities, connectivity, and heterogeneity can be overcome. This paper proposes a novel three-tier architecture, called EdgeSphere, which harnesses resources of the edge devices, to analyze the data in situ at the edge. In contrast to the state-of-the-art cloud and mobile applications, EdgeSphere applications span across cloud, edge gateways, and edge devices. At its core, EdgeSphere builds on Apache Mesos to optimize resources usage and scheduling. EdgeSphere has been applied to practical scenarios and this paper describes the engineering challenges faced as well as innovative solutions.