Virtualization for Distributed Ledger Technology (vDLT)

Yu, F. Richard; Liu, Jianmin; He, Ying; Si, Pengbo; Zhang, Yanhua

doi:10.1109/access.2018.2829141

Cited by 104 publications

(32 citation statements)

References 17 publications

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“…With DLT, we will have the Internet of value. DLT has great potential to create new foundations for our economic and social systems by efficiently establishing trust among people and machines, reducing cost, and increasing the use of resources [40]. IOTA, as the most prominent distributed ledger project, whose goal is to become the very fundamental layer of such society, is challenging the looming paradigm shift.…”

Section: Resultsmentioning

confidence: 99%

Indoor Air-Quality Data-Monitoring System: Long-Term Monitoring Benefits

Sun

Zheng

Villalba-Díez

et al. 2019

Sensors

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Indoor air pollution has been ranked among the top five environmental risks to public health. Indoor Air Quality (IAQ) is proven to have significant impacts on people’s comfort, health, and performance. Through a systematic literature review in the area of IAQ, two gaps have been identified by this study: short-term monitoring bias and IAQ data-monitoring solution challenges. The study addresses those gaps by proposing an Internet of Things (IoT) and Distributed Ledger Technologies (DLT)-based IAQ data-monitoring system. The developed data-monitoring solution allows for the possibility of low-cost, long-term, real-time, and summarized IAQ information benefiting all stakeholders contributing to define a rich context for Industry 4.0. The solution helps the penetration of Industrial Internet of Things (IIoT)-based monitoring strategies in the specific case of Occupational Safety Health (OSH). The study discussed the corresponding benefits OSH regulation, IAQ managerial, and transparency perspectives based on two case studies conducted in Spain.

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Section: Resultsmentioning

confidence: 99%

Indoor Air-Quality Data-Monitoring System: Long-Term Monitoring Benefits

Sun

Zheng

Villalba-Díez

et al. 2019

Sensors

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“…By this way, the throughput of the blockchain has been significantly improved. Yu et al in [10] considered a virtualization approach in distributed ledger technology (DLT). They abstract the underlying resources, such as hardware, compute, storage, network, and so on, as logical resources.…”

Section: Adaptive Blockchain Architecturementioning

confidence: 99%

“…According to the work in [10], there are several layers in the existing blockchain, namely data layer, network layer, consensus layer, ledger topology layer, incentive layer, privacy layer, contract layer, and application layer. Each layer has its enabling resources to facilitate its functions.…”

Section: Adaptive Enabling Resourcesmentioning

confidence: 99%

Deep Reinforcement Learning Empowered Adaptivity for Future Blockchain Networks

Qiu

Ren

Cao

et al. 2021

IEEE Open J. Comput. Soc.

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Recently, blockchain has elicited escalating attention from academia to industry. However, blockchain is still in its initial stage, and remains a great number of nontrivial problems to be delved before being used as a generic platform. The most intractable one is the scalability problem. The deep reinforcement learning empowered adaptivity can help the blockchain network break through the bottleneck. In this paper, we study a deep reinforcement learning empowered adaptivity approach for future blockchain networks, so as to improve the scalability and meet the requirements of different users. Specifically, rather than using one consensus protocol as the best fit one, the blockchain networks launch different consensus protocols, based on users' quality of service (QoS) requirements. To this end, we quantify four consensus protocols. Additionally, the blockchain networks are heavily hampered by the limited computation and bandwidth resources. We also dynamically allocate computation and bandwidth resources to the blockchain networks. Then we formulate these thress items, i.e., the selection of consensus protocols, computation resource, and network bandwidth resource, as a joint optimization problem. A deep reinforcement learning approach is used to solve this problem. Simulation results are presented to show the effectiveness of our proposed scheme.

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“…In this scheme, each node just stores a part of each transaction thereby storage cost was reduced. In addition, a virtualization approach was proposed for distributed ledger technology [10]. Aforementioned works just consider the storage and distributed ledger management for common blockchians.…”

Section: Related Workmentioning

confidence: 99%

Application-Aware Consensus Management for Software-Defined Intelligent Blockchain in IoT

Dong

Ota

et al. 2020

IEEE Network

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Currently, Internet of Things (IoT) has become a important carrier of blockchains, which not only makes blockchain more ubiquitous but also improves the security of IoT. Consensus is the core component of blockchains with various forms, which raises following challenges. Dynamic management and configuration of the consensuses in a blockchain are required due to the IoT applications have high dynamics. Moreover, a IoT node is usually reutilized by various applications in different blockchains, which leads the IoT node should be switched frequently to cross consensuses in different blockchains. To address this, a software-defined blockchain architecture is proposed to realized the dynamic configurations for blockchains. Then, consensus function virtulization approach with applicationaware work flow are proposed, which can abstract and manager various consensus resources. Next, a transfer learning based intelligent scheme is deigned to implement the application-layer packet analysis and perform the efficient management of virtualized consensus resources. Experiment results indicate the feasibility of the proposed scheme. This work is significant to enhance the flexibility and extendibility of blockchains in IoT. Index Terms-Blockchain, internet of things (IoT), consensus, virtualization.

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Virtualization for Distributed Ledger Technology (vDLT)

Cited by 104 publications

References 17 publications

Indoor Air-Quality Data-Monitoring System: Long-Term Monitoring Benefits

Indoor Air-Quality Data-Monitoring System: Long-Term Monitoring Benefits

Deep Reinforcement Learning Empowered Adaptivity for Future Blockchain Networks

Application-Aware Consensus Management for Software-Defined Intelligent Blockchain in IoT

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