Con-Pi: A Distributed Container-Based Edge and Fog Computing Framework

Edge and Fog computing paradigms overcome the limitations of cloud-centric execution for different latency-sensitive Internet of Things (IoT) applications by offering computing resources closer to the data sources. Small single-board computers (SBCs) like Raspberry Pis (RPis) are widely used as computing nodes in both paradigms. These devices are usually equipped with moderate speed processors and provide support for peripheral interfacing and networking, making them well suited to deal with IoT-driven operations, such as data sensing, analysis, and actuation. However, these small Edge devices are constrained in facilitating multitenancy and resource sharing. The management of computing and peripheral resources through centralized entities further degrades their performance and service quality significantly. To address these issues, a fully distributed framework, named Con-Pi, is proposed in this work to manage resources at the Edge or Fog environments. Con-Pi exploits the concept of containerization and harnesses Docker containers to run IoT applications as microservices. The software system of the proposed framework also provides a scope to integrate different IoT applications, resource and energy management policies for Edge and Fog computing. Its performance is compared with the state-of-the-art frameworks through real-world experiments. The experimental results show that Con-Pi outperforms others in enhancing response time and managing energy usage and computing resources through its distributed offloading model. Further, we have developed an automated pest bird deterrent system using Con-Pi to demonstrate its suitability in developing practical solutions for various IoT-enabled use cases, including smart agriculture.

Automated summary

Edge and Fog computing paradigms offer computing resources closer to data sources, overcoming the limitations of cloud-centric execution. Small single-board computers like Raspberry Pis are widely used in these paradigms, making them suitable for IoT-driven operations. However, these devices are constrained in facilitating multitenancy and resource sharing. To address this, a fully distributed framework named Con-Pi is proposed, which utilizes containerization and Docker containers to manage resources in Edge and Fog environments. Experimental results demonstrate that Con-Pi outperforms other frameworks in terms of response time, energy usage management, and computing resource allocation. Additionally, Con-Pi has been successfully applied to develop a practical pest bird deterrent system for IoT-enabled applications, such as smart agriculture.