Benchmarking Blockchain Interactions in Mobile Edge Cloud Software Systems
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A4 Artikkeli konferenssijulkaisussa
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Authors
Date
2021
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Mcode
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Language
en
Pages
19
213-231
213-231
Series
Benchmarking, Measuring, and Optimizing - Third BenchCouncil International Symposium, Bench 2020, Revised Selected Papers, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 12614 LNCS
Abstract
As blockchain becomes an essential part of many software systems in the edge and cloud, the developer starts to treat blockchain features like commodity software components that can be integrated into edge and cloud software systems. For the developer it is quite challenging to determine, customize, and evaluate suitable blockchain features for software systems in the edge and cloud environments. In this paper, we conceptualize important blockchain interactions in mobile edge computing software systems (MECSS) and present generic techniques for evaluating these interactions. We determine different interaction patterns for different deployments of compute resources and networks. We abstract and represent application-level mobile edge computing (MEC) features and blockchain features to create MECSS deployment models to be coupled with testbed deployments for benchmarking application-level interactions within application contexts. Based on that, we develop a generic framework for building and executing benchmarks of application-level blockchain interactions within MECSS. We will demonstrate our framework for vehicle-to-everything communication scenarios with two main blockchain technologies, Hyperledger Fabric and Ethereum, using various types of compute resources in edge and cloud infrastructures.Description
Keywords
Benchmark, Blockchain, Edge computing, Microservices, Testing
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Citation
Truong, H L & Rydzi, F 2021, Benchmarking Blockchain Interactions in Mobile Edge Cloud Software Systems . in F Wolf & W Gao (eds), Benchmarking, Measuring, and Optimizing - Third BenchCouncil International Symposium, Bench 2020, Revised Selected Papers . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12614 LNCS, Springer, pp. 213-231, International Symposium on Benchmarking, Measuring, and Optimizing, Virtual, Online, 15/11/2020 . https://doi.org/10.1007/978-3-030-71058-3_13