A Peer-to-Peer Architecture for Distributed Data Monetization in Fog Computing Scenarios

Abstract

Modern IoT deployments do require considerable investments that might only be justified if the data being gathered could be monetized, which leads to the need for a digital data marketplace. In many cases, the provider of the IoT data needs to process it locally for data curation, aggregation, stream processing, etc. At the same time, the consumer could be interested in nearby data. This scenario resembles a fog computing architecture where companies require being able, keeping data under their control, to securely make it available to other companies in a peer-to-peer fashion, without needing a cloud intermediary (like traditional marketplaces do), thus maximizing the locality of the processing and avoiding the existence of a bottleneck when the intermediary makes the data delivery for accounting purposes. Nevertheless, this imposes a hard requirement: by not having a central marketplace, the peers (seller and customer) need to trust each other, which, in turn, requires enforcing a nonrepudiation schema. In this paper, the authors propose a distributed peer-to-peer architecture for such a data marketplace that takes advantage of the architectural fundamentals of fog computing, in which data processing, filtering, and stream based event generation is done in a fog node along with the data, and where relationships, both commercial agreements and data delivery, are performed directly between producers and consumers without the need of mutual trust thanks to the usage of blockchain principles (e.g., distributed ledger, consensus mechanism). The proposed architecture is validated through a case study involving a set of key issues regarding nonrepudiation commonly identified when moving from a centralized marketplace to a distributed one. Moreover, it is shown that the proposed solution does not bring in any limitation with regard to a centralized marketplace solution, in terms of pricing models (subscriptions, pay-per-use, etc.) or usage conditions (contract duration, updates rate, etc.).

Business Data Sharing through Data Marketplaces: A Systematic Literature Review

“…The discussion in the architecture category is primarily dominated by blockchain-based systems, which relates to the development of peer-to-peer and decentralized data marketplaces [27,28]. Specifically, the blockchain systems are applied to specific contexts such as the automotive domain [29,30], private data sharing [31], Internet of Things (IoT) [32][33][34][35], or smart cities [36]. In other cases, blockchain-based systems are employed for proposing auditing schema [37], credit scoring [38], data transaction integrity [39], and Proof of Usage (PoU) algorithm [40].…”

A distributed reliable collusion‐free algorithm for selecting multiple coordinators in IOTA using fog computing

“…In Reference 47, a peer‐to‐peer distributed architecture is proposed for the data market using fog computing in which a fog node is responsible for data processing, filtering, and stream‐based event generation. In this architecture, relationships, both commercial agreements and data delivery, are performed directly between producers and consumers without the need of a central trust authority.…”

Decentralized Personal Data Marketplaces: How Participation in a DAO Can Support the Production of Citizen-Generated Data

“…The use of DLTs has been proposed for the implementation of data marketplaces to take advantage of the following advantages [43,44]: (i) no need to rely on third party platforms, (ii) better resilience against network partitioning and single point of failure, and (iii) privacy-preserving mechanisms [45]. Most of the related work investigated the data distribution through DLTs, focusing in particular on the use of off-chain storage based on DFS with data links referenced in DLTs [6,35,45].…”