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arXiv · 1907.02602

MetaAnalysis of Methods for Scaling Blockchain Technology for Automotive Uses

Parth Singhal·Siddharth Masih
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Abstract

The automotive industry has seen an increased need for connectivity, both as a result of the advent of autonomous driving and the rise of connected cars and truck fleets. This shift has led to issues such as trusted coordination and a wider attack surface have come to light, leading to higher costs and bureaucratic interventions. Due to the increasing adoption of connected vehicles, as well as other connected infrastructure, trustless peer to peer systems including blockchain are being explored as potential solution to this efficiency problem. All the while, scalability is still a significant concern for industry players. Current blockchain based systems have difficulty scaling: Bitcoin can only process seven transactions per second (tx/s) whereas Ethereum's fifteen tx/s is not a major improvement. Combined with the high cost of consensus and low throughput, such platforms are unusable with the mobility sector. This paper will address the latest advances in the field that aim to resolve parts of this problem as well as inform its readers about the scalability technologies that could push blockchain automotive infrastructure into the mainstream. This paper will also introduce the theoretical tools and advancements that, if implemented, could bring the mobility industry closer toward adopting efficient, scalable, and cost effective decentralized solutions.

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BibTeXRIS

Parth Singhal, Siddharth Masih. 2019-07-04. MetaAnalysis of Methods for Scaling Blockchain Technology for Automotive Uses. https://arxiv.org/abs/1907.02602

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