2014/11/10 by Philipp Leitner, Leitner, Philipp, Juergen Cito +1 · 4 citations
Computer Science · #Blockchain Technology Applications and Security #Cloud Computing and Resource Management #Distributed #FOS: Computer and information sciences #IoT and Edge/Fog Computing #Parallel #Software System Performance and Reliability #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.1411.2429
openalex publication_date 2014/11/10 · arxiv created 2016/01/19 · arxiv updated 2016/01/20 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
Benchmarking the performance of public cloud providers is a common research topic. Previous research has already extensively evaluated the performance of different cloud platforms for different use cases, and under different constraints and experiment setups. In this paper, we present a principled, large-scale literature review to collect and codify existing research regarding the predictability of performance in public Infrastructure-as-a-Service (IaaS) clouds. We formulate 15 hypotheses relating to the nature of performance variations in IaaS systems, to the factors of influence of performance variations, and how to compare different instance types. In a second step, we conduct extensive real-life experimentation on Amazon EC2 and Google Compute Engine to empirically validate those hypotheses. At the time of our research, performance in EC2 was substantially less predictable than in GCE. Further, we show that hardware heterogeneity is in practice less prevalent than anticipated by earlier research, while multi-tenancy has a dramatic impact on performance and predictability.