September 26, 2021

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Machine Learning Enhanced Blockchain Consensus with Transaction Prioritization for Smart Cities. (arXiv:2107.10242v1 [cs.CR])

In the given technology-driven era, smart cities are the next frontier of
technology, aiming at improving the quality of people’s lives. Many research
works focus on future smart cities with a holistic approach towards smart city
development. In this paper, we introduce such future smart cities that leverage
blockchain technology in areas like data security, energy and waste management,
governance, transport, supply chain, including emergency events, and
environmental monitoring. Blockchain, being a decentralized immutable ledger,
has the potential to promote the development of smart cities by guaranteeing
transparency, data security, interoperability, and privacy. Particularly, using
blockchain in emergency events will provide interoperability between many
parties involved in the response, will increase timeliness of services, and
establish transparency. In that case, if a current fee-based or
first-come-first-serve-based processing is used, emergency events may get
delayed in being processed due to competition, and thus, threatening people’s
lives. Thus, there is a need for transaction prioritization based on the
priority of information and quick creation of blocks (variable interval block
creation mechanism). Also, since the leaders ensure transaction prioritization
while generating blocks, leader rotation and proper election procedure become
important for the transaction prioritization process to take place honestly and
efficiently. In our consensus protocol, we deploy a machine learning (ML)
algorithm to achieve efficient leader election and design a novel dynamic block
creation algorithm. Also, to ensure honest assessment from the followers on the
blocks generated by the leaders, a peer-prediction-based verification mechanism
is proposed. Both security analysis and simulation experiments are carried out
to demonstrate the robustness and accuracy of our proposed scheme.