A Blockchain-Enabled Ecosystem for Distributed Electricity Trading in Smart City

Guo, Jianxiong; Ding, Xingjian; Wu, Weili

doi:10.1109/jiot.2020.3015980

Cited by 63 publications

(30 citation statements)

References 26 publications

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“…For the analysis of telemetric networks, parts of the graph theory were used [ 22 ]. The topology of such networks can be defined by a formula describing geometrical random graphs [ 9 ]:

where V is a set of vertices, E is a set of edges, and R is set of radii determining the transmission range.…”

Section: Methodsmentioning

confidence: 99%

“…Their most important features are digital and computerized management of energy production and distribution;, automatic smart security systems; lighting and heating control; management of car parks; fast data transmission using the latest wireless technologies in the 5G network; municipal serviceless meters and usage sensors with digital water, electricity, and gas distribution management systems; smart medical care systems remote life quality management and improvement such as systems of e-participation in various forms of cultural, sporting, leisure, and social activity; and surveillance systems, biometric systems, and safety systems for terrorist and criminal threats, etc. [ 8 , 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

“…A data concentrator collecting the information from Smart Meter (SM) devices is one of the basic components of ICT systems [ 9 ]. Usually, it is installed next to an MV/LV transformer, hence its name Transformer Station Data Concentrator (TSC) [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…These are Power Line Communication (PLC) and M-bus. The M-bus technology, designed for the reading of various kinds of metering devices, is used in Smart Metering only in last-mile network with direct hubs—Local Metering Concentrators (LMCs)—to which multiple SM devices can be connected through the use of M-bus [ 9 , 15 , 16 ]. LMC communicates with TSC by the use of the RF or the PLC technology.…”

Section: Introductionmentioning

confidence: 99%

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Selection of the Optimal Smart Meter to Act as a Data Concentrator with the Use of Graph Theory

Kiedrowski

2021

Entropy

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Changing the construction of mart Meter (SM) devices, more specifically equipping them with more than one communication module, facilitates the elimination of a Transformer Station Data Concentrator (TSC) module, moving its function to one of the SMs. The opportunity to equip a chosen device in an additional communication module makes it possible to use it as an acquisition node. The introduction of this solution creates a problem with the optimum selection of the above-mentioned node out of all the nodes of the analyzed network. This paper suggests the criterion of its location and, as per the criterion, the way of conduct using the elements of the graph theory. The discussion is illustrated with the examples of the possibility to use the method for the optimization of the architecture of the network. The described method makes it possible to choose the location of a backup acquisition node as well as locate intermediary nodes (signal repeaters) in case of a failure (removal) of some SM devices. In the era of the common introduction of dispersed telemetric systems requiring an adequate level of performance and reliability of information transmission, the offered method can be used for the optimization of the structures of Smart Grids.

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“…For the analysis of telemetric networks, parts of the graph theory were used [ 22 ]. The topology of such networks can be defined by a formula describing geometrical random graphs [ 9 ]:

where V is a set of vertices, E is a set of edges, and R is set of radii determining the transmission range.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Selection of the Optimal Smart Meter to Act as a Data Concentrator with the Use of Graph Theory

Kiedrowski

2021

Entropy

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“…Guo et al [36] proposed a PoW consensus mechanism with stacks to high latency in traditional methods under a blockchain-based electricity trading ecosystem. Samy et al [37] proposed a protected blockchain model utilizing a PoW algorithm to secure the information created by smart meters.…”

Section: Smart Gridsmentioning

confidence: 99%

Approaches towards Blockchain Innovation: A Survey and Future Directions

2021

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A blockchain is a decentralized peer to peer platform which provides security services based on some key concepts, namely authentication, confidentiality, integrity and authorization. It is the process of recording and keeping track of the resources without the intervention of a centralized authority. This paper provides an overview of blockchains, the structure of blockchains, consensus algorithms, etc., It compares the algorithms based on their utility and limitations. Though blockchains provide secure communication, there are some minimal data leaks which are discussed. Various security issues in blockchains are discussed such as denial of service attacks, etc., In addition to security, some other blockchain challenges are presented like scalability, reliability, interoperability, privacy and consensus mechanisms for integration with AI, IoT and edge computing. This paper also explains about the importance of blockchains in the fields of smart healthcare, smart grid, and smart financial systems. Overall, this paper gives the glimpse of various protocols, algorithms, applications, challenges and opportunities that are found in the blockchain domain.

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The impact of mobility on physical layer security in 5G uRLLC

Zheng

et al. 2022

Int J of Intelligent Sys

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Due to the openness nature of wireless medium, security issues have increasingly become a bottleneck that restricts the development of ultra‐reliable and low‐latency communications (uRLLCs). Physical layer security (PLS) technique has been proposed to fulfill the security and confidentiality of information transmission by exploiting the characteristics of the wireless channel, which caters to the features of uRLLC. Furthermore, PLS also shows great practicality in artificial intelligence field, especially in wireless intelligent networks. However, the previous works on the study of PLS ignored the significance of mobility and limited packet length constraint required by uRLLC for satisfying low latency, in this paper, we investigate the impact of mobility on the secrecy performance of uRLLC by using the Random WayPoint (RWP) model and the Random Direction (RD) model. Specifically, with the tools of stochastic geometry, to observe the impact of key system parameters on the secrecy performance, we establish the closed‐form expression of connection outage probability, secrecy outage probability, and decoding error probability‐based secrecy transmission capacity (DEP‐STC). Furthermore, we derive the condition that achieves a positive DEP‐STC under two moving models, which can offer the network designer some greatly significant insights into achieving perfect secrecy. Simulations validate our derived theoretical results, and indicate that RWP moving receiver can obtain a higher security level than RD moving one, while RWP eavesdropper can lead to a lower security.

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A Blockchain-Enabled Ecosystem for Distributed Electricity Trading in Smart City

Cited by 63 publications

References 26 publications

Selection of the Optimal Smart Meter to Act as a Data Concentrator with the Use of Graph Theory

Selection of the Optimal Smart Meter to Act as a Data Concentrator with the Use of Graph Theory

Approaches towards Blockchain Innovation: A Survey and Future Directions

The impact of mobility on physical layer security in 5G uRLLC

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