Consortium Blockchain-Based Federated Sensor-Cloud for IoT Services

IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Sudip Misra;Aishwariya Chakraborty;Ayan Mondal;Dhanush Kamath
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引用次数: 0

Abstract

This work addresses the problem of ensuring service availability, trust, and profitability in sensor-cloud architecture designed to Sensors-as-a-Service (Se-aaS) using IoT generated data. Due to the requirement of geographically distributed wireless sensor networks for Se-aaS, it is not always possible for a single Sensor-cloud Service Provider (SCSP) to meet the end-users requirements. To address this problem, we propose a federated sensor-cloud architecture involving multiple SCSPs for provisioning high-quality Se-aaS. Moreover, for ensuring trust in such a distributed architecture, we propose the use of consortium blockchain to keep track of the activities of each SCSP and to automate several functionalities through Smart Contracts. Additionally, to ensure profitability and end-user satisfaction, we propose a composite scheme, named BRAIN, comprising of two parts. First, we define miner's score to select an optimal subset of SCSPs as miners periodically. Second, we propose a modified multiple-leaders-multiple-followers Stackelberg game-theoretic approach to decide the association of an optimal subset of SCSPs to each service. Thereafter, we evaluate the performance of BRAIN by comparing with three existing benchmark schemes through simulations. Simulation results depict that BRAIN outperforms existing schemes in terms of profits and resource consumption of SCSPs, and price charged from end-users.
联盟基于区块链的物联网服务联邦传感器云
这项工作解决了使用物联网生成的数据确保传感器即服务(Se-aaS)传感器云架构中服务可用性、信任和盈利能力的问题。由于Se-aaS需要地理分布的无线传感器网络,单个传感器云服务提供商(SCSP)并不总是能够满足最终用户的需求。为了解决这个问题,我们提出了一个包含多个scsp的联合传感器云架构,用于提供高质量的Se-aaS。此外,为了确保对这种分布式架构的信任,我们建议使用财团区块链来跟踪每个SCSP的活动,并通过智能合约自动化一些功能。此外,为了确保盈利能力和最终用户满意度,我们提出了一个名为BRAIN的复合方案,由两部分组成。首先,我们定义了矿工的得分,以周期性地选择一个最优的scsp子集作为矿工。其次,我们提出了一种改进的多领导者-多追随者Stackelberg博弈论方法来确定每个服务的最优scsp子集的关联。然后,我们通过仿真比较了三种现有的基准方案,对BRAIN的性能进行了评估。模拟结果表明,从利润和scsp的资源消耗以及向最终用户收取的价格来看,BRAIN方案优于现有方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Cloud Computing
IEEE Transactions on Cloud Computing Computer Science-Software
CiteScore
9.40
自引率
6.20%
发文量
167
期刊介绍: The IEEE Transactions on Cloud Computing (TCC) is dedicated to the multidisciplinary field of cloud computing. It is committed to the publication of articles that present innovative research ideas, application results, and case studies in cloud computing, focusing on key technical issues related to theory, algorithms, systems, applications, and performance.
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