Scalable Edge Computing Cluster Using a Set of Raspberry Pi: A Framework
Gabrielle Evan Farrel, Widhi Yahya, Achmad Basuki, Kasyful Amron, Reza Andria Siregar · 2023
In the context of edge computing, a cluster of small single-board computers like Raspberry Pi could serve as robust servers. These clusters not only offer robust server capabilities but also exhibit a remarkable versatility in handling incoming data streams from a multitude of sensors within the Internet of Things (IoT) ecosystem, particularly in underserved rural areas. Simultaneously, they can seamlessly double up as servers for web-based applications tailored to the specific requirements of small businesses. However, the operational context of such an edge computing cluster can present challenges. For instance, dynamic load fluctuations, ranging from high to low demands, may lead to performance service degradation or underutilized services. This is a typical problem in distributed computing environments, where the heterogeneity of devices, dynamic conditions, and reliability of connections can create scalability issues. This paper addresses these challenges through a selective set of integrated software suites aiming to autoscale an edge computing cluster. The software suites consist of a lightweight Kubernetes distribution called K3s, with an automation framework executed through Ansible. Rigorous testing, primarily focused on web-based applications, has showcased the efficacy of this approach. A compelling comparison has been drawn between this optimized edge computing setup and conventional desktop-based servers, emphasizing superior power efficiency and commendable performance levels. The service scaling can reduce power consumption by up to 45%.