Internet of Things (IoT) are being adopted for industrial and manufacturing applications such as manufacturing automation, remote machine diagnostics, prognostic health management of industrial machines and supply cha...Internet of Things (IoT) are being adopted for industrial and manufacturing applications such as manufacturing automation, remote machine diagnostics, prognostic health management of industrial machines and supply chain management. Cloud-Based Manufacturing is a recent on-demand model of manufacturing that is leveraging IoT technologies. While Cloud-Based Manufacturing enables on-demand access to manufacturing resources, a trusted intermediary is required for transactions between the users who wish to avail manufacturing services. We present a decentralized, peer-to-peer platform called BPIIoT for Industrial Internet of Things based on the Block chain technology. With the use of Blockchain technology, the BPIIoT platform enables peers in a decentralized, trustless, peer-to-peer network to interact with each other without the need for a trusted intermediary.展开更多
The adopters of IoT face challenges with the surging Internet-based attacks on their IoT assets and inefficiencies within the technology. Unfortunately, IoT is overly distributed, still evolving and facing implementat...The adopters of IoT face challenges with the surging Internet-based attacks on their IoT assets and inefficiencies within the technology. Unfortunately, IoT is overly distributed, still evolving and facing implementation and security challenges. Given the above scenario, we argue that the IoT network should always be decentralized design, and security should be built by design. The paper is the design and construction of a decentralized IoT security framework, with the goal of making emerging IoT systems more resilient to attacks and supporting complex communication and resource sharing. The framework improves efficiency and scalability in IoT, exposes vulnerable subsystems and components as possible weak links to system compromise, and meets the requirements of a heterogeneous computing environment. Other features of the framework including efficient resource sharing, fault tolerance, and distributed storage support the Internet of Things. We discuss the design requirements and carry out the implementation of Proof of Concept and evaluation of our framework. Two underlying technologies: the actor model and the blockchain were used for the implementation. Our reason for choosing the actor model and blockchain is to compare its suitability for IoT integration in parallel. Hence, evaluation of the system is performed based on computational and memory efficiency, security, and scalability. We conclude from the evaluations that the actor-based implementation has better scalability than the block-chain-based implementation. Also, the blockchain seems to be computationally more intensive than the actors and less suitable for IoT systems.展开更多
联邦学习(Federated learning,FL)通过分布式协同训练实现多车辆联合建模,在保护数据隐私的同时,有效支持车联网(Internet of vehicles,IoV)中的交通优化、拥堵治理等应用。然而,传统FL在动态异构的IoV环境中面临中心化架构脆弱和网络...联邦学习(Federated learning,FL)通过分布式协同训练实现多车辆联合建模,在保护数据隐私的同时,有效支持车联网(Internet of vehicles,IoV)中的交通优化、拥堵治理等应用。然而,传统FL在动态异构的IoV环境中面临中心化架构脆弱和网络不稳定等挑战。区块链技术的去中心化共识和不可篡改特性为IoV-FL提供了理想的解决方案。围绕区块链赋能下的IoV-FL展开综述,介绍IoV、区块链与IoV-FL的基础概念,分析IoV-FL的系统架构与关键应用场景,并梳理传统方法在隐私安全、系统鲁棒性与可扩展性等方面的局限;从模型更新验证、系统可扩展性、激励机制和知识共享4个维度,系统整理已有研究工作中区块链赋能IoV-FL的关键技术方案,探讨IoV-FL在隐私与安全、存储开销、网络吞吐率、设备与数据异构等方面仍面临的关键挑战;最后,从隐私保护增强、资源利用优化以及系统协同等方面展望未来研究方向。展开更多
The inclusion of blockchain in smart homes increases data security and accuracy within home ecosystems but presents latency issues that hinder real-time interactions. This study addresses the important challenge of bl...The inclusion of blockchain in smart homes increases data security and accuracy within home ecosystems but presents latency issues that hinder real-time interactions. This study addresses the important challenge of blockchain latency in smart homes through the development and application of the Blockchain Low Latency (BLL) model using Hyperledger Fabric v2.2. With respect to latency, the BLL model proposes the optimization of the following fundamental blockchain parameters: transmission rate, endorsement policy, batch size, and batch timeout. After conducting hypothesis testing on system parameters, we found that transactions per second (tps) of 30, OutOf (2) endorsement policy, in which any two of five peers endorse a batch size of 10 and batch timeout of 1 s, considerably decrease latency. The BLL model achieved an average latency of 0.39 s, approximately 30 times faster than Ethereum’s average latency of 12 s, thereby enhancing the efficiency of blockchain-based smart home applications. The results of this study demonstrate that despite introducing certain latency issues, proper selection of parameters in blockchain configurations can eliminate these latency problems, making blockchain technology more viable for real-time Internet of Things (IoT) applications such as smart homes. Future work involves applying the proposed model to a larger overlay and deploying it in real-world smart home environments using sensor devices, enhancing the given configuration to accommodate a large number of transactions, and adjusting the overlay in line with the complexity of the network. Therefore, this study provides practical recommendations for solving the latency issue in blockchain systems, relates theoretical advancements to real-life applications in IoT environments, and stresses the significance of parameter optimization for maximum effectiveness.展开更多
文摘Internet of Things (IoT) are being adopted for industrial and manufacturing applications such as manufacturing automation, remote machine diagnostics, prognostic health management of industrial machines and supply chain management. Cloud-Based Manufacturing is a recent on-demand model of manufacturing that is leveraging IoT technologies. While Cloud-Based Manufacturing enables on-demand access to manufacturing resources, a trusted intermediary is required for transactions between the users who wish to avail manufacturing services. We present a decentralized, peer-to-peer platform called BPIIoT for Industrial Internet of Things based on the Block chain technology. With the use of Blockchain technology, the BPIIoT platform enables peers in a decentralized, trustless, peer-to-peer network to interact with each other without the need for a trusted intermediary.
文摘The adopters of IoT face challenges with the surging Internet-based attacks on their IoT assets and inefficiencies within the technology. Unfortunately, IoT is overly distributed, still evolving and facing implementation and security challenges. Given the above scenario, we argue that the IoT network should always be decentralized design, and security should be built by design. The paper is the design and construction of a decentralized IoT security framework, with the goal of making emerging IoT systems more resilient to attacks and supporting complex communication and resource sharing. The framework improves efficiency and scalability in IoT, exposes vulnerable subsystems and components as possible weak links to system compromise, and meets the requirements of a heterogeneous computing environment. Other features of the framework including efficient resource sharing, fault tolerance, and distributed storage support the Internet of Things. We discuss the design requirements and carry out the implementation of Proof of Concept and evaluation of our framework. Two underlying technologies: the actor model and the blockchain were used for the implementation. Our reason for choosing the actor model and blockchain is to compare its suitability for IoT integration in parallel. Hence, evaluation of the system is performed based on computational and memory efficiency, security, and scalability. We conclude from the evaluations that the actor-based implementation has better scalability than the block-chain-based implementation. Also, the blockchain seems to be computationally more intensive than the actors and less suitable for IoT systems.
文摘联邦学习(Federated learning,FL)通过分布式协同训练实现多车辆联合建模,在保护数据隐私的同时,有效支持车联网(Internet of vehicles,IoV)中的交通优化、拥堵治理等应用。然而,传统FL在动态异构的IoV环境中面临中心化架构脆弱和网络不稳定等挑战。区块链技术的去中心化共识和不可篡改特性为IoV-FL提供了理想的解决方案。围绕区块链赋能下的IoV-FL展开综述,介绍IoV、区块链与IoV-FL的基础概念,分析IoV-FL的系统架构与关键应用场景,并梳理传统方法在隐私安全、系统鲁棒性与可扩展性等方面的局限;从模型更新验证、系统可扩展性、激励机制和知识共享4个维度,系统整理已有研究工作中区块链赋能IoV-FL的关键技术方案,探讨IoV-FL在隐私与安全、存储开销、网络吞吐率、设备与数据异构等方面仍面临的关键挑战;最后,从隐私保护增强、资源利用优化以及系统协同等方面展望未来研究方向。
文摘The inclusion of blockchain in smart homes increases data security and accuracy within home ecosystems but presents latency issues that hinder real-time interactions. This study addresses the important challenge of blockchain latency in smart homes through the development and application of the Blockchain Low Latency (BLL) model using Hyperledger Fabric v2.2. With respect to latency, the BLL model proposes the optimization of the following fundamental blockchain parameters: transmission rate, endorsement policy, batch size, and batch timeout. After conducting hypothesis testing on system parameters, we found that transactions per second (tps) of 30, OutOf (2) endorsement policy, in which any two of five peers endorse a batch size of 10 and batch timeout of 1 s, considerably decrease latency. The BLL model achieved an average latency of 0.39 s, approximately 30 times faster than Ethereum’s average latency of 12 s, thereby enhancing the efficiency of blockchain-based smart home applications. The results of this study demonstrate that despite introducing certain latency issues, proper selection of parameters in blockchain configurations can eliminate these latency problems, making blockchain technology more viable for real-time Internet of Things (IoT) applications such as smart homes. Future work involves applying the proposed model to a larger overlay and deploying it in real-world smart home environments using sensor devices, enhancing the given configuration to accommodate a large number of transactions, and adjusting the overlay in line with the complexity of the network. Therefore, this study provides practical recommendations for solving the latency issue in blockchain systems, relates theoretical advancements to real-life applications in IoT environments, and stresses the significance of parameter optimization for maximum effectiveness.
