Data Exchange Scheme Research Articles

ARTIFICIAL INTELLIGENCE IN LABOUR RELATIONS: A THREAT TO HUMAN RIGHTS OR NEW OPPORTUNITIES?

This article explores the possibility of using artificial intelligence in the field of labour relations. Modern technologies provide new opportunities, but at the same time, they give rise to a number of complex issues, solving new approaches to the realization of the right to work and proper social security by able-bodied citizens, which is important today, when Ukraine is defending its sovereignty and independence from military aggression by the Russian Federation. The use of machine learning algorithms and systems can lead to significant improvements related to the professional training of labour resources, management of production processes, labour protection and other aspects of labour relations.We came to the conclusion that the modernization of labour law involves expanding the circle of participants in labour relations and revising the meaning of the term "employee". Thus, the presence or absence of access to technology will create new forms of inequality in the interaction between "employee-to-employee" and "worker-robot (AI)".A proactive approach is proposed to mitigate the consequences of possible threats to the use of artificial intelligence in labour relations through an in-depth study of all possible threats arising in connection with the use of modern technologies. A proposal is made to take as a basis the international experience of using AI in the social structure of the state and adapt it to the life of the state, which, in turn, will contribute to the promotion of important theses on the quality and accessibility of data at the country level, and in cities in particular, promoting participation in data exchange schemes at the level of the private and public sectors.

A privacy-aware authentication and usage-controlled access protocol for IIoT decentralized data marketplace

Data is ubiquitous, powerful and valuable today. With vast instalments of Industrial Internet-of-Things (IIoT) infrastructure, data is in abundance albeit sitting in organizational silos. Data Marketplaces have emerged to allow monetization of data by trading it with interested buyers. While centralized marketplaces are common, they are controlled by few and are non-transparent. Decentralized data marketplaces allow the democratization of rates, trading terms and fine control to participants. However, in such a marketplace, ensuring privacy and security is crucial. Existing data exchange schemes depend on a trusted third party for key management during authentication and rely on a ‘one-time-off’ approach to authorization. This paper proposes a user-empowered, privacy-aware, authentication and usage-controlled access protocol for IIoT data marketplace. The proposed protocol leverages the concept of Self-Sovereign Identity (SSI) and is based on the standards of Decentralized Identifier (DID) and Verifiable Credential (VC). DIDs empower buyers and give them complete control over their identities. The buyers authenticate and prove claims to access data securely using VC. The proposed protocol also implements a dynamic user-revocation policy. Usage-controlled based access provides secure ongoing authorization during data exchange. A detailed performance and security analysis is provided to show its feasibility.

Distributed Integral Convex Optimization-Based Current Control for Power Loss Optimization in Direct Current Microgrids

Due to the advantages of fewer energy conversion stages and a simple structure, direct current (DC) microgrids are being increasingly studied and applied. To minimize distribution loss in DC microgrids, a systematic optimal control framework is proposed in this paper. By considering conduction loss, switching loss, reverse recovery loss, and ohmic loss, the general loss model of a DC microgrid is formulated as a multi-variable convex function. To solve the objective function, a top-layer distributed integral convex optimization algorithm (DICOA) is designed to optimize the current-sharing coefficients by exchanging the gradients of loss functions. Then, the injection currents of distributed energy resources (DERs) are allocated by the distributed adaptive control in the secondary control layer and local voltage–current control in the primary layer. Based on the DICOA, a three-layer control strategy is constructed to achieve loss minimization. By adopting a peer-to-peer data-exchange strategy, the robustness and scalability of the proposed systematic control are enhanced. Finally, the proposed distribution current dispatch control is implemented and verified by simulations and experimental results under different operating scenarios, including power limitation, communication failure, and plug-in-and-out of DERs.

Performance Optimization of a Blockchain-Enabled Information and Data Exchange Platform for Smart Grids

Exchanging information and data within smart grids is crucial to improve interoperability among system users. Traditional cloud-based data exchange schemes are centralized on a single trusted third-party platform. The schemes consequently suffer from single-point failure, a lack of data protection, and uncontrolled access. Blockchain enables data exchange in a decentralised and secure manner. A new platform is proposed in this work for exchanging data within smart grids using blockchain. It allows users to securely exchange data without losing ownership. This platform provides solutions to three critical problems: privacy, scalability, and user ownership. Particularly, the blockchain-based smart contract technology gives participants the programmability to access data. All interactions are authenticated and recorded by the other participants in the tamper-resistant blockchain network. Furthermore, the performance of the proposed blockchain platform is enhanced by integrating it with an artificial neural network (ANN). The proposed method is used to predict the network’s throughput and latency, and the network administrator uses these predicted values to change the network’s settings for a high throughput and low latency. Throughout the results, the proposed model achieves performance improvements in blockchain-enabled information and data exchange and adapts well to the dynamics of smart grids.

Lightweight Integrity Preserving Scheme for Secure Data Exchange in Cloud-Based IoT Systems

The information obtained from external sources within the cloud and the resulting computations are not always reliable. This is attributed to the absence of tangible regulations and information management on the part of the information owners. Although numerous techniques for safeguarding and securing external information have been developed, security hazards in the cloud are still problematic. This could potentially pose a significant challenge to the effective adoption and utilization of cloud technology. In terms of performance, many of the existing solutions are affected by high computation costs, particularly in terms of auditing. In order to reduce the auditing expenses, this paper proposes a well-organised, lightweight system for safeguarding information through enhanced integrity checking. The proposed technique implements a cryptographic hash function with low-cost mathematic operations. In addition, this paper explores the role of a semi-trusted server with regard to smart device users. This facilitates the formal management of information prior to distribution through the IoT-cloud system. Essentially, this facilitates the validation of the information stored and exchanged in this environment. The results obtained show that the proposed system is lightweight and offers features such as a safeguarding capability, key management, privacy, decreased costs, sufficient security for smart device users, one-time key provision, and high degree of accuracy. In addition, the proposed method exhibits lower computation complexity and storage expenses compared with those of other techniques such as bilinear map-based systems.

BSDCE-IoV: Blockchain-Based Secure Data Collection and Exchange Scheme for IoV in 5G Environment

The Internet of Vehicles (IoV) is a network that connects vehicles and their environment: in-built devices, pedestrians, and infrastructure through the Internet using heterogeneous access technologies. During communication between vehicles, roadside units, and control rooms, data confidentiality and privacy are critical issues that require effective measures. Several works have been proposed for securing IoV environments based on vehicles-to-infrastructure authentication; However, some schemes have security vulnerabilities, while others have shown efficiency issues. Due to its decentralization, stability, and transaction tracking capabilities, Blockchain as an emerging technology presents a potential solution for IoV security. This article provides an in-depth examination of the benefits of blockchain for a 5G-based IoV environment. In particular, we propose and evaluate a novel blockchain-based secure data exchange (BSDCE-IoV) scheme based on Elliptic Curve Cryptography algorithm. Our solution is designed to eliminate several potential attacks that pose a threat to the IoV environment. Deep examination using the Real-or-Random oracle model and Scyther tool, in addition to the informal security analysis, validates the scheme regarding security and privacy. The Multi-precision Integer and Rational Arithmetic Cryptographic Library (MIRACL) assesses the computational and communication overhead. Computational and communicative overheads were also evaluated using the Multi-precision Integer and Rational Arithmetic Cryptographic Library (MIRACL). BSDCE-IoV shows higher performance in terms of security, functionality, and time delay than a number of recent selective work in IoV security.

Enabling Energy Trading in Cooperative Microgrids: A Scalable Blockchain-Based Approach With Redundant Data Exchange

Blockchain has recently been regarded as an important enabler for building secure energy trading in microgrid systems because of its inherent features of distributively providing immutable data record, storage, and sharing across networks in a peer-to-peer (P2P) manner. However, designing highly efficient and scalable blockchain-enabled energy trading mechanisms is extremely challenging because of the unique features of microgrid systems, e.g., bandwidth-constrained and high-latency communications and large-scale renewable energy source (RES) integration. To address this challenge, in this article, we propose a novel scalable blockchain-based energy trading framework for cooperative microgrid systems, which include four planes, i.e., data plane, consensus plane, smart plane, and application plane. Different from the existing solutions without consideration of network transmission, these four planes are designed with the capability of perceiving the status of block generation and transmission over interrupted P2P networks, and thus proactively improving the consensus process to guarantee the reliability of energy trading in cooperative microgrids. Meanwhile, built on this framework, a novel redundant data exchange strategy is proposed to improve the scalability of block creation with the presence of large-scale RES penetration and interrupted and dynamic communication links. Simulation results show that the proposed system framework outperforms the benchmark blockchain solutions. Furthermore, we investigate the potential applications of the proposed solutions in the practical microgrid systems to facilitate a clear understanding of the mechanisms of the proposed solutions.

Power Grid Multi-protocol Network Topology Based on Data Exchange Strategy

With the combination of Internet of Things technology and smart grid, there are more and more application scenarios of Internet of Things in power system, which makes the whole power system more informationized and intelligent. In this paper, an intelligent data switching technology for power communication network based on multi-protocol label is proposed. The link structure model of mobile core network is constructed, and the TDMA protocol of the multi-protocol intelligent data switching node is designed by using route detection method. The dynamic routing decision and node rotation scheduling of the mobile core network are realized, and the intelligent data exchange performance is improved. Finally, the simulation experiment of the intelligent data exchange protocol is carried out, and the comparative experiment between the proposed method and other methods is carried out, which shows the superior performance of the proposed method in improving the intelligent data exchange capability of the mobile core network.

Internet of things based smart city design using fog computing and fuzzy logic

• “Internet of Things based Smart City Design using Fog Computing and Fuzzy Logic”. • An edge computing paradigm using human interactions for their decision-making process. • Employs probabilistic history-based parameters that keep track of node interactions. • Context-aware smart paradigm considering predictability ratios. • A nature-inspired algorithm used to make the routing considerations. • A fuzzy rule-based system using power-buffer capacity-based index to make classes. The prevalence of IoT based technology in contemporary society allows for the planning of smart city infrastructure with individually owned devices as participating nodes in a social smart network. Edge computing application into such an IoT network facilitates the distributed computing framework by bringing the computational application closer to the end-users in form of Fog sub-networks, comprising the local participating end-user IoT nodes as service requesters and specialized servers catering to the requests, modelled for the infrastructure category they are delivering (Smart healthcare, ITS, Smart architecture, etc.). Opportunistic-based last-mile connectivity between the Fog servers and participating nodes aides the dynamicity of the topology for efficient information. Aiding the same, the proposed edge computing enabled, sustainable, opportunistic IoT-based intuitive data exchange, collection and operation scheme that employs a dynamic routing procedure that considers human interactions, their movement patterns and their decision-making process. The proposed scheme employs probabilistic history-based parameters that keep track of node interactions. The interactions are modelled on the Firefly PSO, allowing exploitation of the social mobility. The Fuzzy logic is used for hop decision making based on the social and attribute-based parameters which mimic intuitive and pragmatic decision making of humans in terms of social interactions and mobility.

From Platform to Knowledge Graph: Evolution of Laboratory Automation.

High-fidelity computer-aided experimentation is becoming more accessible with the development of computing power and artificial intelligence tools. The advancement of experimental hardware also empowers researchers to reach a level of accuracy that was not possible in the past. Marching toward the next generation of self-driving laboratories, the orchestration of both resources lies at the focal point of autonomous discovery in chemical science. To achieve such a goal, algorithmically accessible data representations and standardized communication protocols are indispensable. In this perspective, we recategorize the recently introduced approach based on Materials Acceleration Platforms into five functional components and discuss recent case studies that focus on the data representation and exchange scheme between different components. Emerging technologies for interoperable data representation and multi-agent systems are also discussed with their recent applications in chemical automation. We hypothesize that knowledge graph technology, orchestrating semantic web technologies and multi-agent systems, will be the driving force to bring data to knowledge, evolving our way of automating the laboratory.

Intelligent Mobile Wireless Network for Toxic Gas Cloud Monitoring and Tracking.

Intelligent wireless networks that comprise self-organizing autonomous vehicles equipped with punctual sensors and radio modules support many hostile and harsh environment monitoring systems. This work’s contribution shows the benefits of applying such networks to estimate clouds’ boundaries created by hazardous toxic substances heavier than air when accidentally released into the atmosphere. The paper addresses issues concerning sensing networks’ design, focussing on a computing scheme for online motion trajectory calculation and data exchange. A three-stage approach that incorporates three algorithms for sensing devices’ displacement calculation in a collaborative network according to the current task, namely exploration and gas cloud detection, boundary detection and estimation, and tracking the evolving cloud, is presented. A network connectivity-maintaining virtual force mobility model is used to calculate subsequent sensor positions, and multi-hop communication is used for data exchange. The main focus is on the efficient tracking of the cloud boundary. The proposed sensing scheme is sensitive to crucial mobility model parameters. The paper presents five procedures for calculating the optimal values of these parameters. In contrast to widely used techniques, the presented approach to gas cloud monitoring does not calculate sensors’ displacements based on exact values of gas concentration and concentration gradients. The sensor readings are reduced to two values: the gas concentration below or greater than the safe value. The utility and efficiency of the presented method were justified through extensive simulations, giving encouraging results. The test cases were carried out on several scenarios with regular and irregular shapes of clouds generated using a widely used box model that describes the heavy gas dispersion in the atmospheric air. The simulation results demonstrate that using only a rough measurement indicating that the threshold concentration value was exceeded can detect and efficiently track a gas cloud boundary. This makes the sensing system less sensitive to the quality of the gas concentration measurement. Thus, it can be easily used to detect real phenomena. Significant results are recommendations on selecting procedures for computing mobility model parameters while tracking clouds with different shapes and determining optimal values of these parameters in convex and nonconvex cloud boundaries.

ТРАНСЛЯЦИЯ ГЕОМЕТРИЧЕСКИХ МОДЕЛЕЙ ОДНОКОНТУРНЫХ ГЕОДЕЗИЧЕСКИХ КУПОЛОВ ИЗ ARCHICAD В НЕЙТРАЛЬНЫЙ STEP ФОРМАТ

The methods of data exchange between CAD and CAE systems are described. The first method is using direct conversion, the second method is using neutral formats. The description of the modular system for designing and analysis the strength and stability of single-contour and double-contour geodesic shells GeoTran is given. The direct translation of geometric models from ArchiCAD to Patran/Nastran / Dytran has the disadvantage of having to develop translators for each data exchange scheme. It is proposed to implement the translation of geometric models in a neutral STEP format, which reduces the number of required translators. It is noted that the STEP format is recognized by various CAE systems that implement the finite element method (Autodesk Mechanical Desktop, Bentley Microstation, CATIA V4, CATIA V5, MSC Patran/Nastran, UGS PLM Solutions NX). The characteristics of the OBJ format used for storing a geometric model in the ArchiCAD CAD system and the STEP format used for data exchange with CAE systems are studied. A translator of geometric models of single-contour geodesic shells from ArchiCAD to STEP format in the Visual Basic programming language has been developed. For this purpose a syntactically oriented approach was used. The translator has a graphical user interface that makes it easier to use. The translator allows you to automate the exchange of data between the ArchiCAD CAD system and various CAE systems designed for strength analysis and supporting import from the STEP format. The applicability of the translator for the exchange of data on geometric models of single-contour geodesic domes with triangular plates between ArchiCAD and the Delcam Exchange converter program is verified. It is demonstrated that the STEP file format generated by the OBJSTEPTranslator is recognized by an external program.

Research on Cross-network Exchange Method of Enterprise Application Business Process Data

To solve the problem of efficient, safe and controllable transfer of enterprise-level application systems’ data across network, this paper proposes a data exchange method for application systems across physically isolated networks. Firstly, the analysis of the cross-network data exchange business model and the design of the business scenario were carried out, and two typical cross-network data exchange business models were condensed. Then, the design of the overall scheme and the detailed technical scheme of cross-network data exchange based on the one-way import device was carried out. Finally, the cross-network ferry middleware system was developed, and the experimental environment of the cross-network data exchange system based on the one-way import device was built, the personnel organization and the leave process information ferry across physically isolated networks were achieved, and the feasibility of cross-network data exchange scheme was verified.

Standardization of Forms and Tools for Inter-machine Interaction in Exchange of Hydrometeorological Data

The necessity of organizing a machine-to-machine data exchange in the Earth sciences for their subsequent interdisciplinary analysis is shown. The barriers that hinder interaction between various information systems are indicated. The requirements, FAIR, for datasets and the principles, TRUST, for data repositories that must be met to effectively exchange data are presented. An ocean data exchange scheme is described, which is used within a pan-European project, SeaDataCloud, and can be proposed for data exchange with the World Data System. International formats of data exchange services and data visualization tools are briefly described. Examples of integration of distributed and heterogeneous data, metadata bases, and information about classifiers used in ESIMO (http://esimo.ru) are considered. An idea of standardizing a format for storing and exchanging data in the form of time series is proposed. In addition to standardization of formats, it is necessary to standardize the common codes and classifiers used in the data exchange and the parameter names from a unified vocabulary. Some prospects of inter-machine interaction are the creation of tools of data exchange with the existing international and national systems and of conveyor data processing ranging from hydrometeorological data collection to their use in business processes.

FAPS: A fair, autonomous and privacy-preserving scheme for big data exchange based on oblivious transfer, Ether cheque and smart contracts

Decision-making plays an increasing important role in our digitalized society, and hence the need for trustworthy data. For example, in a traditional trading process, a trusted middle person generally helps to arbitrate any dispute between two or more parties involved in the trading. However, having such a trusted middle person can be labor-intensive, increases transaction costs, and lacks fairness during arbitration due to the subjectivity of the middle person. While we can avoid the need for a middle person using smart contract-based approaches, there are other limitations (e.g., fairness and privacy preservation) that need to be addressed. In this paper, we present a fair scheme for big data exchanging that allows buyers and sellers to autonomously and fairly complete transactions, without involving any third-party middle person. Specifically, our scheme uses smart contracts and oblivious transfer protocol, in combination with our proposed Ether cheque system. Smart contracts are used to achieve transaction fairness, autonomy and trading timing control. The oblivious transfer protocol helps us to preserve the privacy of transactions. We use Ether cheque to improve the fairness of the transaction and make the transaction more convenient. Also, our proposed approach can facilitate the identification of a cheating party.

Transmission Power System Modeling by Using Aggregated Distributed Generation Model Based on a TSO—DSO Data Exchange Scheme

By integrating distributed energy resources (DER, mostly renewable energy sources) in the depth of the distribution network transmission system operators (TSOs), planning and control of transmission systems has been greatly hindered due to the lack of knowledge about the circumstances at the transmission and distribution network’s interface and the lack of coordination with the distribution system operator (DSO). By adopting the Commission Regulation (EU) 2017/1485 (System Operational Guideline—SOGL) establishing a guideline on electricity transmission system operation, harmonized rules on system operation for TSOs, DSOs and significant grid users (SGUs) are set out, inter alia, in order to provide a clear legal framework for the exchange of necessary data and information between the aforementioned subjects. In this paper, the methodology of DER representation at the interface of the transmission and distributed system is presented, with the indicated interactive data exchange between TSO and DSO, for running and analyzing the operation of the entire power system (PS) in real and extended real time. The proposed methodology was tested on a real model of the Croatian transmission PS and with representative DER in the depth of the distribution network.

Privacy preservation with unequal data exchange strategy in participatory sensing*

In participatory sensing, participants contribute sensing data to task center. However, the task center is not always trustworthy. It may try to profile the participants by data mining, which is a great threat to the privacy of participants. To solve this problem, three collaborative data exchange strategies are studied. Participants exchange sensing data before upload to the task center. The mixed data protect the participants’ privacy from data mining by the task center. The simulations show that the unequal data exchange strategy is more efficient than the full exchange strategy because it considers both the tradeoff between privacy preservation and the cost of data exchange.

Enhancement of microgrid operation by considering the cascaded impact of communication delay on system stability and power management

Power management, system stability and communication structure are three key aspects of microgrids (MGs) that have been explored in many research studies. However, the cascaded effect of communication structure on system stability followed by the impact of stability on the power management has not been fully explored in the literature yet and needs more attention. This paper not only explores this cascaded impact, but also provides a comprehensive platform to optimally consider three layers of MG design and operation from this perspective. For generation cost minimization and stability assessment, the proposed platform uses an adaptive particle swarm optimization (PSO) while a new class of data exchange scheme based on IEC 61850 protocol is proposed to reduce the communication time delays among the inverters of distributed generations and the MG control center. This paper also considers the system stability using small-signal model of a MG in a real-time manner as an embedded function in the PSO. In this context investigations have been conducted by modeling an isolated MG with solar farm, fuel cell generator and micro-turbine in MATLAB Simulink. Detailed simulation results indicate the proposed power and stability management method effectively reduces the MG generation cost through maximizing the utilization of the available renewable generations while considering system stability.

Heuristic-based opportunistic network coding at potential relays in multi-hop wireless networks

Network Coding (NC) has been a solution scheme for data exchange in communications that amalgamate data packets, especially in multi-hop wireless networks. Existing studies demonstrated the use of NC in wireless networks by evaluating its key advantages. The store-code-forward approach of network coding at relay nodes brings out the most relevant benefits in the performance metrics, such as power, throughput, and goodput in communication. COPE is a fundamental protocol, which exploits link diversity and the broadcast nature of a wireless medium using the XOR criteria for data packet amalgamation. COPE is unsuccessful in the exploration of maximum compatibility packets through which opportunistic routing can be maximized. Hence, to identify maximum compatibility packets at relay nodes, the paper presents the uses of Artificial Bee Colony (ABC) optimization algorithm integrated with shortest path planning technique for optimal routing. The authors have successfully demonstrated the validation of Routing-aware Heuristic-based Opportunistic Network Coding (RHONC) mechanism in the multi-hop wireless network. The paper evaluates the proposed mechanism, and enhances throughput gain, goodput gain, and reduced energy consumption against COPE.

Fast Data-Obtaining Algorithm for Data Assimilation with Large Data Set

Data assimilation is an analysis technique which combines observations and the numerical results from theoretical models to deduce more realistic and accurate data. It is widely used in investigations of the atmosphere, ocean and land surface. Due to the complicated data structure of the inputs from dynamical models and the increase of the amount of model data, the parallelization of data assimilation suffers from high overhead on file reading and data communication. In this paper, we propose a flexible parallel data access approach for reading a large number of data from disks firstly. Using this approach, the data access conflict is avoided successfully, and the frequency of disk addressing operations is also decreased significantly. Next, we design a communication-avoiding strategy to reduce the communication volume at the cost of some additional computations. Furthermore, we present a “pipe-flow” scheme for data exchange to conduct conflict-free message passing. Consequently, a fast data-obtaining algorithm is developed for the data assimilation. Our experiments show that the fast data-obtaining algorithm gains a performance of $$5\times $$ speedup compared with the baseline, which is excellent at data-obtaining for the parallel data assimilation. Due to the reduction of disk addressing operations, the new approach achieves $$6\times $$ speedup on average for the file reading process. Since a large amount of data movement can be avoided, the new approach achieves $$2.7\times $$ speedup on average for the communication between processors.