Building microclouds at the network edge with the Cloudy platform

Edge computing enables new types of services which operate at the network edge. There are important use cases in pervasive computing, ambient intelligence and the Internet of Things (IoT) for edge computing. In this demo paper we present microclouds deployed at the networks edge in the Guifi.net community network leveraging an open extensible platform called Cloudy. The demonstration focuses on the following aspects: The usage of Cloudy for end users, the services of Cloudy to build microclouds, and the application scenarios of IoT data management within microclouds.Peer ReviewedPostprint (author's final draft

On participatory service provision at the network edge with community home gateways

Edge computing is considered as a technology to enable new types of services which operate at the network edge. There are important use cases in ambient intelligence and the Internet of Things (IoT) for edge computing driven by huge business potentials. Most of today's edge computing platforms, however, consist of proprietary gateways, which are either closed or fairly restricted to deploy any third-party services. In this paper we discuss a participatory edge computing system running on home gateways to serve as an open environment to deploy local services. We present first motivating use cases and review existing approaches and design considerations for the proposed system. Then we show our platform which materializes the principles of an open and participatory edge environment, to lower the entry barriers for service deployment at the network edge. By using containers, our platform can flexibly enable third-party services, and may serve as an infrastructure to support several application domains of ambient intelligence.Peer ReviewedPostprint (author's final draft

Codesign of edge intelligence and automated guided vehicle control

Abstract. In recent years, edge Artificial Intelligence (AI) coupled with other technologies such as autonomous systems have gained a lot of attention. This work presents a harmonic design of Autonomous Guided Vehicles (AGV) control, edge intelligence, and human input to enable autonomous transportation in industrial environments. The AGV has the capability to navigate between a source and destinations and pick/place objects. The human input implicitly provides the preferences of the destination and exact drop point, which are derived from the AI at the network edge and shared with the AGV over a wireless network. Design and integration of autonomous control of AGV, edge intelligence, and communication therein are carried out in this work and presented as a unified demonstration. The demonstration indicates that the proposed design of hardware, software, and intelligence design achieves the Technology Readiness Level (TRL) of range 4–5