An edge-based architecture to support the execution of ambience intelligence tasks using the IoP paradigm

Abstract

In an IoP environment, edge computing has been proposed to address the problems of resource limitations of edge devices such as smartphones as well as the high-latency, user privacy exposure and network bottleneck that the cloud computing platform solutions incur. This paper presents a context management framework comprised of sensors, mobile devices such as smartphones and an edge server to enable high performance, context-aware computing at the edge. Key features of this architecture include energyefficient discovery of available sensors and edge services for the client, an automated mechanism for task planning and execution on the edge server, and a dynamic environment where new sensors and services may be added to the framework. A prototype of this architecture has been implemented, and an experimental evaluation using two computer vision tasks as example services is presented. Performance measurement shows that the execution of the example tasks performs quite well and the proposed framework is well suited for an edge-computing environment.

BECA: A Blockchain-Based Edge Computing Architecture for Internet of Things Systems

“…In another study by Alanezi and Mishra [35], an architecture based on edge computing and an IoT framework was used to devise and execute an ambient intelligent task such as the automated discovery of new sensors and services at the network's edge. In their approach, mobile devices use Bluetooth Low Energy (BLE) to discover services offered by the edge server.…”