Towards Benchmarking IaaS and PaaS Clouds for Graph Analytics

Conference Paper (2014)
Author(s)

Alexandru Iosup (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Mihai Capota (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Tim Hegeman (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Yong Guo (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Wing Lung Ngai (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Ana Lucia Varbanescu (Universiteit van Amsterdam)

Merijn Verstraaten (Universiteit van Amsterdam)

Research Group
Data-Intensive Systems
DOI related publication
https://doi.org/10.1007/978-3-319-20233-4_11 Final published version
More Info
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Publication Year
2014
Language
English
Research Group
Data-Intensive Systems
Pages (from-to)
109-131
Publisher
Springer
ISBN (print)
978-331920232-7
ISBN (electronic)
978-3-319-20233-4
Event
Big Data Benchmarking (2014-08-05 - 2014-08-06), Cham, Potsdam, Germany
Downloads counter
242

Abstract

Cloud computing is a new paradigm for using ICT services—only when needed and for as long as needed, and paying only for service actually consumed. Benchmarking the increasingly many cloud services is crucial for market growth and perceived fairness, and for service design and tuning. In this work, we propose a generic architecture for benchmarking cloud services. Motivated by recent demand for data-intensive ICT services, and in particular by processing of large graphs, we adapt the generic architecture to Graphalytics, a benchmark for distributed and GPU-based graph analytics platforms. Graphalytics focuses on the
dependence of performance on the input dataset, on the analytics algorithm,
and on the provisioned infrastructure. The benchmark provides components for platform configuration, deployment, and monitoring, and has been tested for a variety of platforms. We also propose a new challenge for the process of benchmarking data-intensive services, namely the inclusion of the data-processing algorithm in the system under test; this increases significantly the relevance of benchmarking results, albeit, at the cost of increased benchmarking duration.