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Offloaded Data Processing Energy Efficiency Evaluation
Volume 35, Issue 3 (2024), pp. 649–669
Pub. online: 24 July 2024      Type: Research Article      Open accessOpen Access
Received
1 September 2023
Accepted
1 July 2024
Published
24 July 2024

Abstract

The growing popularity of mobile and cloud computing raises new challenges related to energy efficiency. This work evaluates four various SQL and NoSQL database solutions in terms of energy efficiency. Namely, Cassandra, MongoDB, Redis, and MySQL are taken into consideration. This study measures energy efficiency of the chosen data storage solutions on a selected set of physical and virtual computing nodes by leveraging Intel RAPL (Running Average Power Limit) technology. Various database usage scenarios are considered in this evaluation including both local usage and remote offloading. Different workloads are benchmarked through the use of YCSB (Yahoo! Cloud Serving Benchmark) tool. Extensive experimental results show that (i) Redis and MongoDB are more efficient in energy consumption under most usage scenarios, (ii) remote offloading saves energy if the network latency is low and destination CPU is significantly more powerful, and (iii) computationally weaker CPUs may sometimes demonstrate higher energy efficiency in terms of J/ops. An energy efficiency measurement framework is proposed in order to evaluate and compare different database solutions based on the obtained experimental results.

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Biographies

Prokhorenko Victor
https://orcid.org/0000-0003-1012-6216
victor.prokhorenko@adelaide.edu.au

V. Prokhorenko received the PhD degree in computer science from The University of South Australia, in 2017. He is a researcher with the Centre for Research on Engineering Software Technologies, The University of Adelaide, Adelaide. He has more than 14 years of experience in software engineering with main areas of expertise, including the investigation of technologies related to software resilience, trust management, and big data solutions hosted within OpenStack and Microsoft Azure cloud platforms.

Babar Muhammad Ali
https://orcid.org/0000-0001-9696-3626
ali.babar@adelaide.edu.au

M.A. Babar is a professor in the School of Computer Science, University of Adelaide. Prof. Babar has established an interdisciplinary research centre called CREST (Centre for Research on Engineering Software Technologies), where he directs the research, education, and engineering activities of more than 25 researchers and engineers. He also leads a theme on architecture and platform for security as a service in the Cyber Security Cooperative Research Centre. Prof. Babar has initiated and led several interdisciplinary R&DI programs in collaboration with industry/govt partners in Australia and Europe. Professor Babar has authored/co-authored more than 280 peer-reviewed papers at premier software journals and conferences. Professor Babar obtained a PhD in computer science and engineering from the school of computer science and engineering of the University of New South Wales, Australia.


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Open access article under the CC BY license.

Keywords
energy measurement NoSQL databases SQL database cloud computing edge computing performance

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