使用区块链和众传感实现按需分散的物联网可收集性市场

Duc-Duy Nguyen, M. Ali
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引用次数: 16

摘要

物联网(IoT)正在产生前所未有的数据量,促进了数据经济的兴起。在这个生态系统下,物联网数据市场(IDM)为物联网数据交易提供了一个在线平台。大多数当前的IDM解决方案都是集中式的,充当数据提供者和使用者之间的中介。它们支持销售和购买数据集合(例如,预先收集的数据集和数据流)。然而,由于这些数据集合是在历史上收集的,没有数据消费者给出的任何优先需求和首选项,因此这些数据集合中的大多数很可能无法满足数据消费者的需求。冗余、数据质量差、不准确和有限的财务激励是现有idm的常见问题,从而使它们在财务上无效。由于物联网数据的时间性质,预收集问题变得更加关键,因为从过去重新收集数据并非易事。本文提出了一个具有新的按需市场模型的新框架,即分散式物联网可收集性数据市场(DCDM)模型。与仅仅将数据收集视为商品的传统IDM模型不同,我们的模型还涉及操作因素,如数据提供者的可用性、可操作性、上下文和地理位置等。这使我们的框架不仅可以交易数据集,还可以交易数据提供者完成收集任务的能力。我们改变游戏规则的方法是使用区块链和众感技术的结合来实现的。我们首先探讨了IDM的“数据可收集性”概念,然后建立了一个模型,将我们的方法部署到物联网环境中。此外,我们还确定了潜在的应用和开放的研究挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enabling On-Demand Decentralized IoT Collectability Marketplace using Blockchain and Crowdsensing
The Internet of Thing (IoT) is generating an unprecedented volume of data, facilitating the rise of the Data Economy. Under this ecosystem, the IoT data marketplace (IDM) provides an online platform for IoT data trading. Most current IDM solutions are centralized, serving as an intermediary between the data provider and consumer. They support selling and buying data collections (e.g. pre-collected data sets and data streams). However, as these data collections are historically collected without having any priory requirements and preferences given by the data consumer, it is very likely that most of these data collections cannot fulfill data consumer requirements. Redundancy, poor data quality, inaccuracy and limited financial incentives are common problems for existing IDMs, thereby making them financially ineffective. Due to the temporal nature of IoT data, the issue of pre-collection becomes even more critical as it is not trivial to re-collect data from the past.This paper presents a novel framework with a new on-demand market model, namely Decentralized IoT Collectability Data Marketplace (DCDM) model. Difference from the conventional IDM models where merely data collections are considered as a commodity, our model also involves operational factors such as data provider availability, operationality, contextual and geographical location etc. This empowers our framework to trade not only the dataset but rather an ability of the data provider to fulfill the collection task. Our game-changing approach is realized using a combination of Blockchain and Crowdsensing techniques. We first explore the concept of ”Data Collectability” for IDM, then build a model to deploy our approach on IoT context. Furthermore, we identify potential applications and open research challenges.
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