Please use this identifier to cite or link to this item: http://theses.ncl.ac.uk/jspui/handle/10443/5554
Title: Decentralised, trustless marketplace for brokered IoT data trading
Authors: Bajoudah, Shaimaa Mohammed A
Issue Date: 2022
Publisher: Newcastle University
Abstract: Trading data as valuable assets has become a trend. The use of real-time data generated from IoT devices provides a new insight into how to conduct a profitable business. As data marketplaces are becoming ubiquitous, it is also becoming clear that IoT data hold value for potential third-party consumers. This work introduces a marketplace for IoT data streams that can unlock such potential value in a scalable way, by enabling any pairs of data providers and consumers to engage in data exchange transactions without any prior assumption of mutual trust. It investigates the use of the power of blockchain technology in automating data trade agreements in a decentralised architecture. We present a marketplace protocol to support trading of streaming data, from the advertising of data assets and the stipulation of legally binding trading agreements, to their fulfilment and payment settlement, and managing trade participants’ reputations. This work has two outcomes: a marketplace model and a reputation model. We present a decentralised, trustless marketplace for brokered IoT data trading, using Blockchain in Ethereum network that enables producers and consumers to start trading in the absence of trust; however, it is managed by a reputation model. Our marketplace is powered by a reputation system that is designed to address participants’ trust and the reputation management of these traders in this marketplace. We mathematically define the reputation model by applying a reputation function to the marketplace participants – either producers or consumers – to quantify their trustworthiness in trading, based on various criteria. We evaluate the marketplace functionalities and its reputation model by designing a marketplace simulator. It is designed to simulate participant trading in the marketplace and how reputations are quantified based on rules and criteria defined in the system protocol. It is configured to replicate the behaviour of multiple pairs of producers and consumers in different trading scenarios and show how reputations are measured in these different scenarios. We experimentally show the trade-off between a trade overhead cost and the level of participant trust. On Blockhain Ethereum Mainnet, our system evaluates the latency of transactions an Ethereum takes to process and confirm our marketplace transactions.
Description: PhD Thesis
URI: http://hdl.handle.net/10443/5554
Appears in Collections:School of Computing

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