Blockchain-Oriented Coalition Formation by CPS Resources: Ontological Approach and Case Study

Kashevnik, Alexey; Teslya, Nikolay

doi:10.3390/electronics7050066

Cited by 14 publications

(16 citation statements)

References 31 publications

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“…In [10], there is a typical maintenance scenario of manufacturing; the data from handwriting and gesture are associated with the CPS; the new problem processing model can be used for feature recognition and data fusion, and then compares with domain knowledge. Reference [11] also proposed the immutable distributed data storage based on blockchain; the multivariate data related to CPS are linked to ontologies, then proceed the deep data fusion, and finally they have optimized the cooperation of heterogeneous mobile robots.…”

Section: A Cpsmentioning

confidence: 99%

Top-Down Human-Cyber-Physical Data Fusion Based on Reinforcement Learning

Chen

Wang

et al. 2020

IEEE Access

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With the development of industrial Internet and artificial intelligence, data fusion in crossdomains and cross-layers have become an inevitable trend. Most of the data fusion involved in the production process of hot rolling are concentrated on the level of sensors, Internet of Things (IoT) and the Internet; but human data are not well integrated. In order to avoid the human factor from becoming the bottleneck of the entire production schedule, this paper proposes a ternary data fusion model based on reinforcement learning algorithm. The related data source from human-cyber-physical space includes: social network, Internet and IoT. By merging the ternary data, a variety of data (including humans') can be quickly calculated to obtain better and faster decisions. In order to achieve automated fusion from ternary data, this paper proposes a method based on reinforcement learning: firstly, the domain ontology used for associating ternary data is reduced and tessellated (dimension reduction), and then the reinforcement learning model is used to form "the new ontology". Compared with resource-intensive global calculations (which may cost a few days), the new method can complete the calculations in minutes. This means that the new method optimizes the data source required for decision-making and improves the efficiency. Finally, the production scheduling of hot rolled steel is used as an example to verify the feasibility of the proposed method. INDEX TERMS human-cyber-physical data fusion, ternary data fusion, cyber-physical system, domain ontology, reinforcement learning

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Section: A Cpsmentioning

confidence: 99%

Top-Down Human-Cyber-Physical Data Fusion Based on Reinforcement Learning

Chen

Wang

et al. 2020

IEEE Access

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“…Coalition is the most highly organized type of collective work organization [7]. Each robot in coalition is considered as an independent agent with its own competencies and goals, which he aims to achieve after the problem solving.…”

Section: Coalition Formationmentioning

confidence: 99%

“…When forming a coalition, it is necessary to take into account the capabilities of robots in such a way that in total they cover all the requirements of the task to be jointly solved. To this end, it is proposed to use an ontology that provides descriptions of the requirements of tasks and the capabilities of robots [7]. An example of an ontology for describing a robot is presented in Figure 1.…”

Section: Coalition Formationmentioning

confidence: 99%

Execution Plan Control in Dynamic Coalition of Robots with Smart Contracts and Blockchain

Teslya

Potryasaev

2020

Information

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The paper presents an approach of the blockchain and smart contracts utilization for dynamic robot coalition creation. The coalition is forming for solving complex tasks in industry applications that requires sequential united actions from the several robots. The main idea is that the process is split into two stages: scheduling and dynamic execution. On the scheduling stage, the coalition is defined based on the correlation of existing tasks and robot equipment, and the execution plan is formed and stored in smart contracts. The second stage is the plan execution. During this stage, smart contract controls how each robot solves its sub-task and whether it solves the sub-task due to the planned moment of time. In case of any deviation from the plan, smart contacts will provide a solution for returning to the plan or for changing the coalition composition with new robots and an execution plan. The prototype for execution control system has been developed based on the Hyperledger Fabric platform.

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“…28 Work has also been done in developing semantics for connecting robotics systems and blockchain networks. 29,30 An ontological framework for resource interaction in blockchainenabled heterogeneous robotic networks was deployed on two kinds of robots: measuring robots and manipulating robots in a cargo delivery application. 28 The measuring robot measured the size of an obstacle and relayed this information to the manipulating robot, which decided if it could overcome the obstacle.…”

Section: Related Workmentioning

confidence: 99%

A Blockchain Enhanced Framework for Social Networking

Murimi

2019

ledger

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Social networking sites have given users unprecedented opportunities for the generation and dissemination of content. A variety of social networking sites exist for different purposes, to afford users a range of anonymous and non-anonymous options for self-expression, and the ability to be a part of a virtual community. These “affordances” enable users to create and share content; however, the ability to partially or wholly detach user identity from the content has resulted in unique challenges for content access and content attribution. This paper proposes a framework for secure, trustworthy social networking that also creates value for user-generated content by using a blockchain-enhanced framework for social networking. This work explains the application of such a framework for collocated spaces of robots and IoT devices and identifies key challenges that result as a consequence of merging social networking sites and blockchain technology.

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Blockchain-Oriented Coalition Formation by CPS Resources: Ontological Approach and Case Study

Cited by 14 publications

References 31 publications

Top-Down Human-Cyber-Physical Data Fusion Based on Reinforcement Learning

Top-Down Human-Cyber-Physical Data Fusion Based on Reinforcement Learning

Execution Plan Control in Dynamic Coalition of Robots with Smart Contracts and Blockchain

A Blockchain Enhanced Framework for Social Networking

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