Blockchain-enabled fog resource access and granting

Liu, Gang; Wu, Jinsong; Wang, Ting

doi:10.23919/icn.2021.0009

Cited by 16 publications

(8 citation statements)

References 5 publications

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“…And how to secure sensitive user information during recommendations is another research direction in our future study. At last, network structure [50][51][52][53] and routine selection [54][55][56][57] are two main components that form a typical social network and influence the performance of short video recommendation network. Therefore, we will continue to refine our work by introducing more social network elements in the future; this way, cold start issues in short video recommendations would be alleviated.…”

Section: Conclusion and Further Discussionmentioning

confidence: 99%

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Liu¹,

Wan²,

Yan³

2023

Computer Modeling in Engineering &Amp; Sciences

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With the popularity of 5G and the rapid development of mobile terminals, an endless stream of short video software exists. Browsing short-form mobile video in fragmented time has become the mainstream of user's life. Hence, designing an efficient short video recommendation method has become important for major network platforms to attract users and satisfy their requirements. Nevertheless, the explosive growth of data leads to the low efficiency of the algorithm, which fails to distill users' points of interest on one hand effectively. On the other hand, integrating user preferences and the content of items urgently intensify the requirements for platform recommendation. In this paper, we propose a collaborative filtering algorithm, integrating time context information and user context, which pours attention into expanding and discovering user interest. In the first place, we introduce the temporal context information into the typical collaborative filtering algorithm, and leverage the popularity penalty function to weight the similarity between recommended short videos and the historical short videos. There remains one more point. We also introduce the user situation into the traditional collaborative filtering recommendation algorithm, considering the context information of users in the generation recommendation stage, and weight the recommended short-form videos of candidates. At last, a diverse approach is used to generate a Top-K recommendation list for users. And through a case study, we illustrate the accuracy and diversity of the proposed method.

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Section: Conclusion and Further Discussionmentioning

confidence: 99%

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Liu¹,

Wan²,

Yan³

2023

Computer Modeling in Engineering &Amp; Sciences

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“…German power company Rheinland Group and Slock.it have developed the "Share&Charge" blockchain platform on which drivers can handle clean energy vehicle-related operations, including allowing drivers to share their charging stations, pay tolls and charging an electric car. The platform relies on Ethereum to operate, especially the smart contract and distributed ledger technology supported by Ethereum, Giraldo et al realized the transparency and trust of billing [15,16]. Specifically, it is to create a token on the blockchain and distribute the mobile value denominated in euros on the token.…”

Section: "Shareandcharge" Blockchain Platformmentioning

confidence: 99%

Blockchain-based Distributed Power Market Trading Mechanism

Cui¹,

He²,

Zhang³

et al. 2022

Computers, Materials &Amp; Continua

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Distributed power market trading has the characteristics of large number of participants, scattered locations, small single trading scale, and point-to-point trading. The traditional centralized power trading model has the problems of large load, low efficiency, high cost, reliance on third parties and unreliable data. With the characteristics of decentralization and nontampering, blockchain can establish a point-to-point trusted trading environment and provide effective solutions to the above problems. Therefore, this paper proposed a distributed power market trading framework based on blockchain. In this framework, the distributed power supply characteristics and trading needs of each participant are analyzed, a complete distributed trading process based on blockchain is designed. In addition, we have studied the key technologies of distributed power market trading. With the goal of power service reputation and maximum revenue of distributed power providers, we have established a matching degree model, a distributed power market trading optimization model, and designed a smart contract-based power market trading optimization strategy and power trading settlement strategy. Finally, we designed experiments to verify the performance of the proposed framework.

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“…As is evident from the above figure, the key attribute of the model has been categorized in line with the three perspectives under examination, notably (i) Blockchain encompasses 6 attributes, namely access control [15][16][17][18], accuracy [4][5][6][7], availability [17,18], immutability [45,46], interoperability [70][71][72], and tamper proofing [11][12][13][14]. (ii) Training provider encompasses 5 attributes, namely confidentiality [5][6][7][8], data integrity [33,34], effectiveness [47,48], privacy, and security [5][6][7].…”

Section: The Proposed Blockchain Framework For Data-sharing Between T...mentioning

confidence: 99%

“…During the past ten years, blockchain technology has emerged, garnering a great deal of interest in both educational [6] and training arenas [15], with the majority of employers utilising external training entities to deliver training for lower-level staff [45]. ere are two key types of training entities [7], namely independent providers and further education colleges, both of which could fall into voluntary [16], private, or public sectors [46].…”

Section: Introductionmentioning

confidence: 99%

The Blockchain Framework for the Sharing of Data between Training Providers Based on the Internet of Things

Alotaibi¹

2022

Scientific Programming

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Blockchain technology is recognised as being a key focus when it comes to modern-day studies and interest on a global scale, with the new block of transactions responsible for the continued growth and expansion of a distributed ledger that details transactional data, complete with immutable and verifiable structures. A greater degree of transparency, privacy, security, and traceability is provided by blockchain when a comparison is drawn with more conventional strategies. As a result of its secure and more progressive elements, blockchain is applied in a number of different arenas, including digital transactions, education, the healthcare industry, the Internet of Things (IoT), trade finance, and the training sector. Importantly, a notable effect on all applied fields has been witnessed as a result of blockchain technology, with data and transactional reliability, as well as privacy, recognised as the most important aspects when it comes to data-sharing in the training arena specifically. Very few models and frameworks are aligned with the guidelines put forth in this sector; as such, this report seeks to consider the pressing need to determine a model and framework to facilitate the sharing of data between training providers in line with the IoT. This study, therefore, centres on the creation of a blockchain model, with the creation of a sole recognition system for professionals seen to be advantageous for all such providers, specifically in the mind of providing a greater degree of clarity and simplification to the system in line with the IoT. The suggested model is focused on a number of different elements that have been identified as a result of studied theories, with consideration of the three different standpoints and professional assessments of 16 unique items.

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Blockchain-enabled fog resource access and granting

Cited by 16 publications

References 5 publications

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Blockchain-based Distributed Power Market Trading Mechanism

The Blockchain Framework for the Sharing of Data between Training Providers Based on the Internet of Things

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