Implementing Virtualization on Single-Board Computers: A Case Study on Edge Computing

Abstract

The widespread adoption of cloud computing has resulted in centralized datacenter structures; however, there is a requirement for smaller-scale distributed infrastructures to meet the demands for speed, responsiveness, and security for critical applications. Single-Board Computers (SBCs) present numerous advantages such as low power consumption, low cost, minimal heat emission, and high processing power, making them suitable for applications such as the Internet of Things (IoT), experimentation, and other advanced projects. This paper investigates the possibility of adopting virtualization technology on Single-Board Computers (SBCs) for the implementation of reliable and cost-efficient edge-computing environments.The results of this study are based on experimental implementations and testing conducted in the course of a case study performed on the edge infrastructure of a financial organization, where workload migration was achieved from a traditional to an SBC-based edge infrastructure. The performance of the two infrastructures was studied and compared during this process, providing important insights into the power efficiency gains, resource utilization, and overall suitability for the organization’s operational needs.

Adaptive Multi-Criteria Selection for Efficient Resource Allocation in Frugal Heterogeneous Hadoop Clusters

“…In [24], Lambropoulos et al explore the use of SBCs like Raspberry Pi 4B for edge computing, demonstrating a successful transition from traditional x86 infrastructure to SBCbased clusters. Despite higher CPU usage and storage latency, the SBC-based setup showed significant power savings, consuming nine times less energy.…”

“…The above-mentioned works highlight the proposition of deploying Hadoop clusters in edge environments with SBCs like Raspberry Pi as a viable option [19][20][21][23][24][25][26][27], driven by cost-effectiveness, energy efficiency, sustainability, and flexibility. Although it may require addressing certain challenges, the benefits in terms of reduced latency, scalability, and sustainability make it a compelling choice for many edge and remote scenarios.…”

Towards Improving YARN performance for Frugal Heterogeneous SBC-based Edge Clusters

“…al. in [25], explore the use of SBCs like Raspberry Pi 4B for edge computing, demonstrating a successful transition from traditional x86 infrastructure to SBC-based clusters. Despite higher CPU usage and storage latency, the SBC-based setup showed significant power savings, consuming nine times less energy.…”

“…The above-mentioned works highlight the proposition of deploying Hadoop clusters in edge environments with SBCs like Raspberry Pi is a viable option [20][21][22][23][24][25][26][27][28], driven by cost-effectiveness, energy efficiency, sustainability and flexibility. Although it may require addressing certain challenges, the benefits in terms of reduced latency, scalability, and sustainability make it a compelling choice for many edge and remote scenarios.…”

Optimizing Hadoop Scheduling in Single-Board-Computer-Based Heterogeneous Clusters

“…By conducting various Hadoop benchmarks such as WordCount, Terasort, DFSIO, etc., and experimenting with different storage configurations, the study shows that Raspberry Pi clusters can successfully manage large workloads, providing a practical alternative to traditional server setups. In their work [7], Lambropoulos et al investigate the use of single-board computers (SBCs) such as Raspberry Pi 4B for edge computing, showcasing a successful shift from conventional x86-based infrastructure to SBC-based clusters. Although this setup experiences increased CPU usage and storage latency, it brings significant energy savings, using just one-ninth of the power compared to traditional systems.…”