Data Transfer Mechanism Research Articles

From data silos to seamless integration and coordination: a data-asset centric approach to smart hospital facility management

PurposeExisting hospital building operations involve numerous information technology applications and complex building systems; therefore, an intelligent facility management (FM) platform is required to ensure their continuous operation. To address the persistent issues of data silos, inefficient data interoperability, and workflow incoordination that have been identified in the current body of FM practice and literature, the present study develops a data-asset (DA) centric FM platform specifically designed for hospital buildings.Design/methodology/approachThis study proposes a semi-customized approach to develop the DA-centric FM platform for hospital buildings. To elucidate the precise function requirements of the hospital FM platform, focus group interviews are employed. By seamlessly integrating the as-built BIM model, IoT sensor data and FM workflow data, the BIM-based DA model with a data transfer mechanism is developed. The development of the FM platform with function modules in a case study is guided by a five-tier architecture and the coordination theory (CT). The case study provides an in-depth introduction to the applications of DA management, space management and maintenance management modules.FindingsThe capabilities of the developed DA-centric hospital FM platform are validated through the case application and user satisfaction survey, which assess data quality, automation level, operation efficiency, flexibility and functionality. For hospital FM activities, this DA-centric FM platform realizes data integration and seamless transformation, optimizes workflow coordination and enhances operation performance.Originality/valueThe initial scholarly contribution is the establishment of the BIM-based DA model, which serves as the data middle platform for continuous data integration, transmission and sharing within the FM platform. Subsequently, under the guidance of the CT, the business process of function modules is designed, improving the intra-module and inter-module workflow coordination. The developed DA-centric FM system along with its performance benchmarking application, assists facility managers and decision-makers in implementing smart operations for hospital buildings and achieving the management goals of safety, efficiency, energy savings and convenience.

Technology Gaps for Monitoring Birds and Marine Mammals at Offshore Wind Facilities

Abstract With increased focus on offshore wind (OSW) as a renewable energy resource in the United States and elsewhere, there are concerns about OSW impacts to wildlife, particularly birds and marine mammals. This study identifies technology gaps and technological research and development (R&D) priorities for monitoring marine mammals and birds for fixed and floating OSW. A synthesis of current monitoring technologies generated two databases (with over 100 technologies) that can be integrated in current technology repositories for renewable energy projects. Generally, the key technology R&D needs are similar for birds and marine mammals. The main exception is that some types of bird technologies are more likely to require direct integration with OSW infrastructure, whereas marine mammal systems tend to operate independently. Priorities to advance wildlife monitoring include improved early communication, harmonization of technologies and data collection for monitoring systems on OSW structures, battery/power access improvements, remote data transfer improvements, and advancements in automated collection and analysis of data. The successful integration of wildlife monitoring systems into OSW infrastructure and operations is dependent on remote access mechanisms for data collection, system maintenance, and data transfer, in order to minimize risks to worker safety in the offshore environment, as well as minimizing costs and disruption to normal operational activities. Application of the results of this study to prioritize and fund technology R&D will help to support statistically robust data collection and practicable integration of monitoring systems into OSW operations and infrastructure.

A Proposal for a Mobility-Control Data Transfer Mechanism Based on a Block Network Utilizing End-to-End Authentication Data

Advances in communications technology have had tremendous influence on network implementation to date, and as communication devices get smaller and technologies more intelligent, a great number of solutions are emerging that converge communications with a multitude of domains. In particular, as transportation modes assisting with mobility have developed, many studies are in the pipeline on the domain of mobility. The development of mobility services has prompted the spread of car sharing, which also highlights the need for a system that controls shared vehicles. The data of such control system can be used not only for the operational management of vehicles but also the management of users in terms of user driving analysis or monitoring safe driving. In addition, it can be utilized in a variety of other applications that analyze traffic flow based on vehicle driving data, determine required vehicle maintenance intervals, or schedule vehicle maintenance in advance. However, if forged/altered by a third party, control data might pose a lot of challenges to data utilization. This study proposes a mechanism that manages control data on a blockchain to enhance the integrity of control data created in the communications process. In this paper, we propose a mechanism for applying a blockchain to the communication process between clients and servers. In the proposed mechanism, platform operators generate and provide independent identification information and identification numbers for users. The identification information and identification numbers are used to prove that the generated blocks were created by specific users. Data generated by clients create a block with a hash including user identification information alongside the user identification number. Verification of the generated block is performed on the platform vendor’s server, validating that the user identification number in the block matches the server-side user identification information and the hash of the data within the block. Thus, even when the contents of the block are shared in a public blockchain environment, user identification information is only held by the server and clients, preventing third parties from impersonating specific users to create data blocks. Furthermore, the verification process of the data includes hashes received from other nearby vehicles, preventing data tampering by the block creator.

Use of multi-agent systems and the Internet of Things to monitor the environment of commercial broiler poultry houses through specific air enthalpy

The intensive production system for broilers requires the availability of an environment (aviary) that promotes an artificial microclimate that favors both animal well-being and productive performance; therefore, monitoring this environment is critical for production success, especially in tropical countries. This criticality opens up a range of research opportunities for monitoring because of the currently available technologies, especially in the areas of the Internet of Things and Expert Systems. Thus, this study presents a proposal for the environmental monitoring of an aviary using an Internet of Things technological apparatus combined with multi-agent systems to monitor climatic variables with the guidance of thermal comfort indicators. The experiment took place in a Cobb broiler aviary located in the countryside of the State of São Paulo, Brazil. With this objective in mind, the production period of Cobb broilers was analyzed through the construction of an Internet of Things system to collect air temperature, relative humidity, and atmospheric pressure variables combined with a data transfer mechanism for cloud recording. These variables were then analyzed by computational agents using the Java programming language with the Jade framework, which generated animal comfort indicators. The results showed that real-time monitoring of environmental variables is possible with the combination of the Internet of Things with agents that can determine animal comfort conditions according to the specific enthalpy of the air through the orchestration of a deliberative agent and with the participation of several reactive agents.

A novel trusted hardware-based scalable security framework for IoT edge devices

The Internet of Things (IoT) devices are pervasively deployed and embedded into our daily lives. Over several years, the massive assimilation of IoT devices has given rise to smart cities, smart factories, smart farms, etc. While IoTs can collect immense amounts of user and environmental information, the lack of adequate security measures is among the major concerns about information security and privacy. With the ever-increasing presence of IoTs, information flow between IoT devices in a single or multi-layered network is becoming increasingly vulnerable to attacks. Although several software-based solutions have been developed over the years that improve the security of resource-constrained IoT devices, there are limited efforts on hardware-oriented IoT security solutions. This paper proposes a Trusted HArdware-based Scalable Secure Architecture (THASSA) for IoT Edge systems. Leveraging standard cryptographic algorithms, THASSA provides a secure mechanism for data transfer and off-loads cryptography operations to trusted hardware. The modularized THASSA architecture allows devices to be added or removed without user intervention. Also, THASSA could be scaled to multiple subsystems using multiple trusted hardware to form IoT clusters with secure data path(s) for mission-critical applications. An experimental study has verified the correctness and effectiveness of THASSA.

Multi-physics code coupling methodology for the simulation of accidental transients in sodium cooled fast reactors

The French Alternative Energies and Atomic Energy Commission (CEA) has played a substantial role in advancing fourth-generation reactor technologies, including Sodium-cooled Fast Reactors (SFR), which are anticipated to offer enhanced efficiency, adaptability, and sustainability compared to existing nuclear technologies. In the context of safety assessment, it is crucial to precisely simulate accidental scenarios like Unprotected Loss Of Flow (ULOF) transients. These transients entail intricate multi-physics interactions within the reactor, particularly within the core, encompassing thermal-hydraulics, reactor physics, and fuel performance (e.g. changes in densities or temperatures will lead to neutronics effects, thus power, then causing feedbacks onto said densities and temperatures).In order to capture those complex phenomena, a multi-physics coupling approach for SFRs, which combines the CATHARE3 code for system scale thermal-hydraulics, the APOLLO3 code for reactor physics, and the GERMINAL V2 code for nuclear fuel performance has been developed at CEA in the recent years.This paper presents a comprehensive methodology of such coupling and its integration into a Verification, Validation and Uncertainty Quantification (VVUQ) process. The first part of the paper provides an introduction to the simulation tools used for the coupling. The following section explains the multi-physics coupling approach, facilitated by CEA’s Collaborative Code Coupling Platform (C3PO), which enables code integration through a Python interface to create a comprehensive simulation model. A detailed examination of the coupling algorithm and data transfer mechanisms is also provided.The generality and reliability of this approach are demonstrated by simulating two accidental transients: the Unprotected Loss Of Flow (ULOF) in the ASTRID reactor and the Loss Of Flow WithOut Scram (LOFWOS) in the Fast Flux Test Facility (FFTF), both corresponding to a primary pump trip without control rods falling. The results show that the proposed multi-physics coupling scheme is effective and robust for SFR simulations. The coupled model enables a more accurate and realistic representation of the complex phenomena occurring in the reactor during an accident.This research underscores the significance of multi-physics coupling in the analysis of SFRs and serves as a valuable point of reference for future SFR studies. The proposed approach offers an efficient way to investigate SFR responses during accidents or incidents, thereby advancing the development of dependable and precise simulation tools for SFR design and evaluation.

A checkpointing mechanism for virtual clusters using memory-bound time-multiplexed data transfers

Transparent hypervisor-level checkpoint-restart mechanisms for virtual clusters (VCs) or clusters of virtual machines (VMs) offer an attractive fault tolerance capability for cloud data centers. However, existing mechanisms have suffered from high checkpoint downtimes and overheads. This paper introduces Mekha, a novel hypervisor-level, in-memory coordinated checkpoint-restart mechanism for VCs that leverages precopy live migration. During a VC checkpoint event, Mekha creates a shadow VM for each VM and employs a novel memory-bound timed-multiplex data (MTD) transfer mechanism to replicate the state of each VM to its corresponding shadow VM. We also propose a global ending condition that enables the checkpoint coordinator to control the termination of the MTD algorithm for every VM in a VC, thereby reducing overall checkpoint latency. Furthermore, the checkpoint protocols of Mekha are designed based on barrier synchronizations and virtual time, ensuring the global consistency of checkpoints and utilizing existing data retransmission capabilities to handle message loss. We conducted several experiments to evaluate Mekha using a message passing interface (MPI) application from the NASA advanced supercomputing (NAS) parallel benchmark. The results demonstrate that Mekha significantly reduces checkpoint downtime compared to traditional checkpoint mechanisms. Consequently, Mekha effectively decreases checkpoint overheads while offering efficiency and practicality, making it a viable solution for cloud computing environments.

Hybrid bioinspired approach for secret sharing algorithm and ownership transfer optimization in cloud based models

It is widely accepted that secret sharing models like Shamir cryptosystem allows cloud designers to deploy highly secure multichannel data transfer mechanisms. But these systems are majorly static, and do not incorporate context-aware share-selection techniques. Moreover, SaaS based cloud deployments require ownership transfers for efficient real-time operations. These ownership transfer mechanisms are backed by selection encryption models assisting in permission-aware data sharing. Scholars have put forward pre-emptive and bioinspired models to accomplish these tasks, but nearly all of them are still sophisticated or demonstrate limited flexibility in real-time scenarios. The proposed structure first gathers cloud logs for various temporal requests and groups them based on IP & resource constraints with the goal of getting around these problems. The modified rules are initially tested on dummy ownership requests, and are later on real-time ownership-transfer scenarios for validation of their efficiency levels based on accuracy of misconfiguration detection, delay needed for processing the requests, consistency of blocking invalid ownership requests, and request throughput levels. Based on this evaluation, The accuracy might be increased by 3.5% using the suggested model, reducing delay by 2.9%, while having 6.4% higher consistency, and 8.3% higher throughput than existing secret sharing & ownership transfer methods under similar deployment scenarios.

The EU–US data privacy framework and the impact on companies in the EEA and USA compared to other international data transfer mechanisms

Third time's a charm? Companies in the European Economic Area, Switzerland and the UK (EEA+) are considering the pros and cons of the third attempt of the EU Commission and US government to establish interoperability between their data protection and privacy law systems, after the demise of the US Safe Harbor Program and the EU–US Privacy Shield. Should US companies register? Are the efforts worth the potential benefits, given that the new programme has already been challenged and may be invalidated like previous programmes for reasons that businesses cannot control? Should companies that were already enrolled in the previous programmes accept automatic enrolment or leave the programme? Can and should companies in the EEA+ rely on EU–US Data Privacy Framework (DPF) registration for international transfers? Or insist on registration in addition to standard contractual clauses (EU SCC 2021) or other compliance mechanisms? Are data transfer impact assessments (DTIAs) still required for transfers to the US? Should they be updated? This paper seeks to help companies find answers to these questions and (I) outlines the background and context of the Adequacy Decision, (II) explains how US companies can join the DPF, (III) discusses the impact of the Adequacy Decision, (IV) summarises requirements for other compliance mechanisms for international data transfers under the GDPR, (V) compares the DPF to other transfer compliance mechanisms and (VI) provides practical considerations and a summary.

Blockchain-Enabled Hyperledger Fabric to Secure Data Transfer Mechanism for Medical Cyber-Physical System: Overview, Issues, and Challenges

This paper proposes a model to address the challenges faced by medical cyber-physical systems (MCPS) by implementing a permissioned blockchain platform. The platform incorporates the unique properties of blockchain into the network of affected systems, including decentralization, transparency, and immutability. The platform also includes a novel technique to secure MCPS through an automated access-control manager. This manager allows users to control who has access to their data, and can be configured to trust a third party if desired. The paper also extends into networked medical device systems, and discusses how the platform can be used to address critical is-sues specific to this field, such as network design. Finally, the paper discusses how various security features can be integrated into ultra-small devices, enhancing the protection of embedded systems. The overall objective of this research is to develop a secure and efficient data transfer mechanism for MCPS. The proposed platform addresses the challenges faced by MCPS by incorporating the unique properties of blockchain.

Horus : Accelerating Kernel Fuzzing through Efficient Host-VM Memory Access Procedures

Kernel fuzzing is an effective technique in operating system vulnerability detection. Fuzzers such as Syzkaller and Moonshine frequently pass highly structured data between fuzzer processes in guest virtual machines and manager processes in the host operating system to synchronize fuzzing-relevant data and information. Since the guest virtual machines’ and the host operating system’s memory spaces are mutually isolated, fuzzers conduct synchronization operations using mechanisms such as Remote Procedure Calls over TCP/IP networks, incurring significant overheads that negatively impact the fuzzer’s efficiency and effectiveness in increasing code coverage and finding vulnerabilities. In this paper, we propose Horus , a kernel fuzzing data transfer mechanism that mitigates the aforementioned data transfer overheads. Horus removes host-VM memory isolation and performs data transfers through copying to and from target memory locations in the guest virtual machine. Horus facilitates such efficient transfers through using fixed stub structures in the guest’s memory space, whose addresses, along with the guest’s RAM contents, are exposed to the host during the fuzzer’s initialization process. When conducting transfers, Horus passes highly-structured non-trivial data between the host and guest instances through copying the data directly to and from the stub structures, reducing the overall overhead significantly compared to that of using a network-based approach. We implemented Horus upon state-of-the-art kernel fuzzers Syzkaller , Moonshine and kAFL and evaluated its effectiveness. For Syzkaller and Moonshine , Horus increased their transfer speeds by 84.5% and 85.8% for non-trivial workloads on average and improved their fuzzing throughputs by 31.07% and 30.62%, respectively. Syzkaller and Moonshine both achieved a coverage speedup of 1.6× through using Horus . For kAFL, Horus improved specifically its Redqueen component’s execution speeds by 19.4%.

MeHLDT: A multielement hash lock data transfer mechanism for on-chain and off-chain

MeHLDT: A multielement hash lock data transfer mechanism for on-chain and off-chain

Blockchain-Based AI-Enabled Industry 4.0 CPS Protection Against Advanced Persistent Threat

Industry 4.0 is all about doing things in a concurrent, secure, and fine-grained manner. IoT edge-sensors and their associated data play a predominant role in today's industry ecosystem. Breaching data or forging source devices after injecting advanced persistent threats (APT) damages the industry owners' money and loss of operators' lives. The existing challenges include APT injection attacks targeting vulnerable edge devices, insecure data transportation, trust inconsistencies among stakeholders, incompliant data storing mechanisms, etc. Edge-servers often suffer because of their lightweight computation capacity to stamp out unauthorized data or instructions, which in essence, makes them exposed to attackers. When attackers target edge servers while transporting data using traditional PKI-rendered trusts, consortium blockchain (CBC) offers proven techniques to transfer and maintain those sensitive data securely. With the recent improvement of edge machine learning, edge devices can filter malicious data at their end which largely motivates us to institute a Blockchain and AI aligned APT detection system. The unique contributions of the paper include efficient APT detection at the edge and transparent recording of the detection history in an immutable blockchain ledger. In line with that, the certificateless data transfer mechanism boost trust among collaborators and ensure an economical and sustainable mechanism after eliminating existing certificate authority. Finally, the edge-compliant storage technique facilitates efficient predictive maintenance. The respective experimental outcomes reveal that the proposed technique outperforms the other competing systems and models.

Adaptive technologies for rapid web interface design of corporate educational systems within the framework of the 1C:Enterprise 8.3 platform

The article discusses technologies for fast web application deployment design based on continuous information exchange with a corporate system developed using the 1C:Enterprise 8.3 platform. We identify data exchange formats between a web application and a software product based on the 1C:Enterprise 8.3 platform to handle the tasks of dynamically generated and adaptable interfaces. The study proposes the concept of a modifiable component-based architecture for the interaction of a web application with commercial data storage and processing systems. This concept makes it possible to implement a dynamic web application interface design and to automate the data management functionality directly from the enterprise solution based on the 1C:Enterprise 8.3 platform. The article formulates the criteria and operating principles for such an application. We have also developed system technologies to design a web application that can be integrated into replicated software solutions permitting control of the mechanisms for dynamic interface design and data transfer from the solution to a web application. The launched application for web application interfaces designing makes it possible to dynamically change the components of web forms as well as determine the details displayed to the user in the output interface. In addition, we describe the principles of dynamic interaction between a web application and the data interface management component. The research enabled us to identify the components of the module for interaction of interfaces with the web application. A conceptual universal control scheme for generating dynamic interfaces has been formulated. It can be implemented to create almost any kind of web forms, including processing incoming data from a web application using the REST interchange in JSON format. The article provides a comparison of interchange formats. We describe implemented IT-projects for organizing a prospective student’s personal account and the applicant’s dynamic rating. These projects are the result of the ideas proposed in the article.

Third Country PNR Mechanisms After the CJEU’s Schrems II Judgment

The article illustrates how the Court of Justice of the European Union (CJEU)’s Schrems II judgment solidified the European court’s approach to European Union (EU) data protection and the issues of data collection and transfer outside EU borders. The judgment rebalances how to arrange the issues containing the collection of private information and the risk to the public without surveillance. Thus, invalidating previously used EU-Third Country data sharing frameworks. Included in this are the Passenger Name Records (PNR), which are used in day-to-day mechanisms of the air industry when sharing bulk data sets with other countries to provide crucial information for anti-terrorism with border protection agencies. Not only does it protect national security, but makes flying safer. Though the EU argues it cannot sacrifice the integrity of individual data autonomy. Due to the Schrems II judgment, most other countries will be unable to pass new EU standards, and data transfer has to be judged on a case-by-case basis, which when looking at the international air industry is unfeasible. By exploring the Schrems II judgment, this article will analyze the third-country data transfer mechanisms and the impact the judgment had on third countries. Air law, PNR, CJEU, Schrems II, Privacy Shield, national security, European Data Protection, data transfer mechanisms, GDPR, Standard Contractual Clauses (SCC)

The Performance of Various Lightweight Block Ciphers FPGA Architectures: A Review

Today most of our devices connected with Internet to assistance us to improve our decisions. The number of people are using wireless and Internet networks increased day by day, which this increased improved the encryption mechanisms for devices and protect user data transfer over an unsecured network. Due to the limited resources for most portable devices, the concept of ubiquitous computing presents must be working terms of security, which contains Confidentiality, Integrity, Authentication, and non-repudiation. In comparison to energy-efficient with cryptography the conventional approaches are expensive and complicated and high-power consumption. The design of lightweight cryptography has solved big number of problem for hardware implementation with the conventional cryptography. In this paper, performance and efficiency depend of architectures review for lightweight block cipher algorithm base of FPGA design and implementation.

Research on General Data Layer Components Model based on Data-Driven

With the continuous deepening of Web applications, more and more people in the front-end field have begun to pay attention to the design of the data layer, which puts forward more and more requirements for the versatility and operability of the data layer. Analyzing the data transmission process, it is found that the data layer has problems such as complex data requests, close data dependencies, and data display differences. In response to the above problems, this paper proposes a data-driven general data layer component model and develops this model with Vue components at the same time. Schema fusion implements a common data transfer mechanism. Based on the component model of the data layer, middleware such as adapters, assemblers, collectors, and converters are designed, and the data layer is operable, universal, and Configurable purpose.

A Blockchain-Based Authentication Solution for 6G Communication Security in Tactile Networks

In this era, the ultimate vision is to transform current technologies into intelligent global environments to facilitate everyday transactions. The emerging Industry 4.0 has introduced promising potential technologies that have expedited the transition of Internet of Things (IoT) into the Internet of Everything (IoE), utilizing the advances in artificial intelligence. Such a transition implies that sensitive data can be effortlessly accessed via the open network used by various domains such as military, business, transportation, medical, and education, leading to potential security concerns. Although a blockchain, along with the above fields, already employs a fast network such as 5G, the explosive growth in the development and implementation of various Industry 4.0-related domains requires significantly faster networking speeds and a secure mechanism for data transfer. This exhibits the need for 6G to meet the requirements of real-time applications, as shown in the graphical representation of the abstract. The bulk of this work was performed on a blockchain, but some methodology was needed that fulfilled security at different levels, such as the process level, data level, and infrastructure level. Our contribution in this work was twofold: first, at the process level, a novel smart contract mechanism was described; and second, at the data level, a digital signature methodology was employed that allowed anonymization to authenticate and secure the blockchain without encryption.

Forecasting the Electricity Capacity and Electricity Generation Values of Wind &Solar Energy with Artificial Neural Networks Approach: The Case of Germany

ABSTRACT Recently, studies on energy estimation have been developing rapidly to increase the efficiency of Wind & Solar energy production-consumption. Artificial Neural Networks, an algorithm based on the human brain and its nervous system inspired by the data transfer and storage mechanism, can work very well as a prediction model. In this study, total Wind & Solar Electricity Capacity (WSEC) and total Wind & Solar Electricity Generation (WSEG) values of Germany, a G8 member and a European country, have been estimated by using Artificial Neural Networks (ANN) method. Population, unemployment, GDP growth and total renewable energy capacity (excluding wind and solar energy total) parameters have been used as input variables in ANN calculations. The use of geographic, socio-economic and technological parameters has strengthened the estimation model. WSEC training and test regressions calculated by ANN have been 1 and 0.99988, respectively. WSEC Mean Absolute Deviation (MAD), Mean Squared Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) parameters have been calculated as 94.783, 62496.807, 249.994 and 0.364, respectively. WSEG training and test regressions values have been 1 and 0.99983, respectively. The WSEG MAD, MSE, RMSE and MAPE parameters have been calculated as 114.406, 59252.128, 243.418 and 0.526, respectively.

Accelerating Deep Learning Using Interconnect-Aware UCX Communication for MPI Collectives

Deep learning workloads on modern multi-graphics processing unit (GPU) nodes are highly dependent on intranode interconnects, such as NVLink and PCIe, for high-performance communication. In this article, we take on the challenge to design an interconnect-aware multipath GPU-to-GPU communication using unified communication X (UCX) to utilize all available bandwidth for both NVLink-based systems and those that use a mixture of NVLink and PCIe. Our proposed multipath data transfer mechanism pipelines and stripes the message across multiple intrasocket communication channels and memory regions to achieve 1.84× higher bandwidth for Open message passing interface (MPI) on NVLink-based systems and 1.23× on NVLink and PCIe systems. We then utilize this mechanism to propose a three-stage hierarchical, pipelined MPI_Allreduce design as well as a flat pipelined two-stage algorithm for two different node topologies. For large messages, our proposed algorithms achieve a high speedup when compared to other MPI implementations. We also observe significant speedup for the proposed MPI_Allreduce with Horovod + TensorFlow with a variety of deep learning models.