On Energy Efficiency and Performance Evaluation of Single Board Computer Based Clusters: A Hadoop Case Study

• Autor(a) principal: Qureshi, Basit
• Data de Publicação: 2019
• Outros Autores: Koubâa, Anis
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/12935
• topic: Green cloud computing; ARM32 single board computers; Hadoop MapReduce; Power consumption; Performance evaluation

Energy efficiency in a data center is a challenge and has garnered researchers interest. In this study, we addressed the energy efficiency issue of a small scale data center by utilizing Single Board Computer (SBC)-based clusters. A compact layout was designed to build two clusters using 20 nodes each. Extensive testing was carried out to analyze the performance of these clusters using popular performance benchmarks for task execution time, memory/storage utilization, network throughput and energy consumption. Further, we investigated the cost of operating SBC-based clusters by correlating energy utilization for the execution time of various benchmarks using workloads of different sizes. Results show that, although the low-cost benefit of a cluster built with ARM-based SBCs is desirable, these clusters yield low comparable performance and energy efficiency due to limited onboard capabilities. It is possible to tweak Hadoop configuration parameters for an ARM-based SBC cluster to efficiently utilize resources. We present a discussion on the effectiveness of the SBC-based clusters as a testbed for inexpensive and green cloud computing research.