APRON: an Architecture for Adaptive Task Planning of Internet of Things in Challenged Edge Networks

摘要

Recently, the growth of Internet of Things (IoT) devices combined with edge computing opened many opportunities for several novel applications. Typical examples are Unmanned Aerial Vehicles (UAV) that are deployed for photogrammetry, surveillance, disaster rapid response and environmental monitoring. A common challenge across all these networked applications is the ability to provide a persistent service - a service able to continuously maintain a high level of performance - responding to events that may change the state of the network, e.g., nodes or link failures. To cope with this challenge, in this paper we propose APRON, an edge cloud-assisted architecture for distributed and adaptive task planning management in a network of IoT devices, e.g., drones. APRON uses a novel planning strategy that, leveraging a Jackson's network model, supports monitoring and control operations while the states of the (edge or cloud) network evolve. By using APRON, edge computing application programmers can design and implement a wide range of IoT task management policies leveraging different protection methodologies across several failure models.