Virtual Layer Research Articles

Envisioning the Future of the Neurosurgical Operating Room with the Concept of the Medical Metaverse.

The medical metaverse can be defined as a virtual spatiotemporal framework wherein higher-dimensional medical information is generated, exchanged, and utilized through communication among medical personnel or patients. This occurs through the integration of cutting-edge technologies such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI), big data, cloud computing, and others. We can envision a future neurosurgical operating room that utilizes such medical metaverse concept such as shared extended reality (AR/VR) of surgical field, AI-powered intraoperative neurophysiological monitoring, and real-time intraoperative tissue diagnosis. The future neurosurgical operation room will evolve into a true medical metaverse where participants of surgery can communicate in overlapping virtual layers of surgery, monitoring, and diagnosis.

Hybrid-Layer Data Storage with High-Orthogonality Random Meta-Channels

Optical data storage (ODS) is a low-cost and high-durability counterpart of traditional electronic or magnetic storage. As a means of enhancing ODS capacity, the multiple recording layer (MRL) method is more promising than other approaches such as reducing the recording volume and multiplexing technology. However, the architecture of current MRLs is identical to that of recording data into physical layers with rigid space, which leads to either severe interlayer crosstalk or finite recording layers constrained by the short working distances of the objectives. Here, we propose the concept of hybrid-layer ODS, which can record optical information into a physical layer and multiple virtual layers by using high-orthogonality random meta-channels. In the virtual layer, 32 images are experimentally reconstructed through holography, where their holographic phases are encoded into 16 printed images and complementary images in the physical layer, yielding a capacity of 2.5 Tbit·cm−3. A higher capacity is achievable with more virtual layers, suggesting hybrid-layer ODS as a possible candidate for next-generation ODS.

HDF5 in the exascale era: Delivering efficient and scalable parallel I/O for exascale applications

Accurately modeling real-world systems requires scientific applications at exascale to generate massive amounts of data and manage data storage efficiently. However, parallel input and output (I/O) faces challenges due to new application workflows and the state-of-the-art memory, interconnect, and storage architectures considered in exascale designs. The storage hierarchy has expanded with node-local persistent memory, solid-state storage, and traditional disk and tape-based storage, thus requiring efficiency at each layer and much more efficient data movement among these layers. This paper discusses how the ExaHDF5 project improved the I/O performance and data management for exascale architectures by enhancing HDF5, a widely used parallel I/O library. The team developed an Asynchronous I/O Virtual Object Layer (VOL) connector that allowed overlapping I/O with computation. They also created a Cache VOL to complement asynchronous I/O by incorporating fast storage layers, such as burst buffer and node-local storage, into the parallel I/O workflow through caching and staging data. Additionally, the team enabled data aggregation and I/O at the node level by using a Subfiling Virtual File Driver (VFD). To demonstrate superior I/O performance with HDF5 at exascale, the ExaHDF5 team collaborated with several exascale applications. In this paper, we show I/O performance improvements for three applications: Cabana (a particle-based simulation library), EQSIM (a regional earthquake simulation software), and E3SM (a climate system modeling library).

Security Evaluation Framework for Virtualised Environments

With the expansion of cloud computing, virtual environments remain susceptible to sophisticated security threats, such as hypervisor vulnerabilities, VM escapes, inter-VM attacks, DoS attacks, and malware injections. Hence, ensuring that virtualised environments are secure, has become increasingly crucial. These threats are particularly affecting as many enterprises which have shifted to online services and remote work. This paper examines the existing frameworks which have been designed to address the existing challenges, their gaps and strengths; and proposes an enhanced security framework that can help to mitigate these threats. The framework was developed following an iterative process encompassing several stages. It has the hypervisor layer, virtual machine layer, network layer, management layer, and monitoring and response layer components. The framework aims to enhance detection capabilities, reduce response times, minimise system performance impact, and lower false positive rates while optimising resource utilisation by providing a practical and effective approach to securing virtualised infrastructures, thereby ensuring the resilience and reliability of cloud-based services.

Fatigue delamination damage analysis in composite materials through a rule of mixtures approach

The present study investigates delamination damage initiation and propagation within a homogenization theory of mixtures, using the concept of virtual layers and virtual interfaces. It eliminates spatial discretization of layers, introducing a resultant damage variable to capture structure’s bulk response under both monotonic and cyclic loads. Fatigue-induced deterioration is classified into sub-critical, critical, and over-critical stages based on interfacial stresses. Calibration is conducted employing the widely-available Wöhler curves for each loading mode independently. An advance-in-time strategy is included in the model to enhance the simulation speed. The reliability of the approach is assessed for crack initiation and propagation separately through standard test coupons, showing good correlation with experimental data in mode I, mode II, and mixed-mode loading conditions. Depending on the calibration procedure adopted, the model is applicable to a wide range of stress ratios. In addition, it could be integrated into any standard finite element framework using the desired number of elements through the thickness regardless of the physical amount of layers. This allows easy modification of stacking sequences or the number of layers within the constitutive law without mesh structure changes, facilitating simulation of large-scale composite laminates with minimal accuracy loss and reduced computational costs.

Virtual body-fitted grid-based immersed boundary method for simulation of thermal flows with Dirichlet and Neumann boundary conditions

In this work, a virtual body-fitted grid-based immersed boundary method (IBM) combined with the thermal lattice Boltzmann flux solver (TLBFS) is proposed to efficiently simulate thermal flows with Dirichlet and Neumann boundary conditions. The method involves generating a virtual body-fitted grid along the immersed boundary and implementing the boundary conditions using a fractional step technique. In the prediction step, the finite-volume TLBFS is used to obtain the predicted flow field on the Eulerian mesh without considering the immersed boundary, while in the correction step, the correction process of the flow field is conducted on the virtual grid. Thus, the effect of the boundary is transferred to the fluid domain through the virtual grid indirectly. For Dirichlet boundary conditions, such as the no-slip condition and the specified temperature condition, the velocity and temperature corrections are considered unknowns and solved through a matrix system formed from enforcing the boundary conditions. As for the Neumann boundary condition, such as the specified heat flux condition, the temperatures at virtual layers inside the immersed body are regarded as unknowns and computed from those at virtual layers outside the wall according to the quadratic distribution. Several benchmark cases including natural, forced, and mixed convection problems are well simulated to validate the method. The numerical results are in good agreement with reference data, demonstrating the capacity of the present method to simulate thermal flows with Dirichlet and Neumann boundary conditions while requiring fewer Lagrangian points and achieving higher computational efficiency.

Resilient Cruise Control of Heterogeneous Platoons Against Byzantine Attacks: Theory and Experiment.

This article studies the problem of the resilient cruise control in heterogeneous vehicle platoons against f -local Byzantine attacks (BAs). Agents under BAs become traitors of the swarm, who try to mislead its neighbors while adopting wrong inputs. Thus, BAs are extremely challenging to be suppressed. This study introduces a novel hierarchical protocol characterized by a virtual twin layer (TL), motivated by the rationale of digital twin. This protocol separates the defense scheme against f -local BAs into two parts: one defense scheme against Byzantine edge attacks (BEAs) via the TL and another scheme against Byzantine node attacks (BNAs) via the cyber-physical layer (CPL). The TL employs a trusted-edge strategy, enhancing the network resilience by incorporating a minimal fraction of the key edges. It is rigorously proven that a TL topology meeting strong (2f+1) -robustness is sufficient for achieving distributed resilient estimation against BEAs. On the CPL, a series of decentralized chattering-free controllers is proposed, guaranteeing the resilient cruise tracking of heterogeneous platoons against exponentially unbounded BNAs. Besides, these controllers can achieve uniformly ultimately bounded convergence. The theoretical results' effectiveness and practicality are validated through a numerical simulation example and an unmanned ground vehicle experiment involving heterogeneous platoons against f -local BAs.

Opening a Virtual Space before the Door of the Law: The Transnational Togani Effect from Silenced to Angels Wear White

Through an examination of what the author calls the transnational Togani effect, which challenges legislative failures across both screens and borders, the author hopes to show how social justice films are deployed as a mode of critique that directly impacts the criminal justice system. The author's analysis of the transnational Togani effect therefore encompasses and connects the dimensions of virtuality and actuality in their interactive relation in the contemporary media environment. The author situates this interactive relationship between the virtual and the actual within a transnational framework because awareness of sexual assault is raised in cross-border contexts that are intertextual and interconnected. Drawing on the Deleuzian notion of the virtual and the actual and Giorgio Agamben's concept of inclusive exclusion, the author suggests that screen intervention is a virtual layer added to heterotopic space that serves as a possible resistance against the entrapment of human subjects by neoliberal governance, in which the law is “in force without significance.” As Deleuze shows, the virtual and the actual are fully real, and the relationship between them takes the form of a circuit. By exploring how the interlocking of virtuality and actuality comes to bear on the legal sphere, this article poses fundamental questions for cinema, or for audiovisual media in general, such as to what extent cinematic critique is capable of opening an alternative space for social justice.

Docker Performance Evaluation across Operating Systems

Docker has gained significant popularity in recent years. With the introduction of Docker Desktop for Windows and macOS, there is a need to determine the impact of the operating system on the performance of the Docker platform. This paper aims to investigate the performance of Docker containers based on the operating system. One of the fundamental goals of this study is to conduct a comprehensive analysis of the Docker architecture. This technology utilizes Linux kernel virtualization mechanisms such as namespaces and cgroups. Upon analyzing the distribution of Docker Desktop for Windows and Docker Desktop for macOS, it was discovered that running the Docker environment on these requires a lightweight virtual machine that emulates the Linux system. This information suggests that the additional virtualization layer may hinder the performance of non-Linux operating systems hosting Docker containers. The paper presents a performance test of the Docker runtime on Linux, Microsoft Windows, and macOS. The test evaluated specific aspects of operating system performance on a MacBook computer with an ×86/64 processor architecture. The experiment carried out examined the performance in terms of CPU speed, I/O speed, and network throughput. This test measured the efficiency of software that utilizes various system resources.

Enhancing Manufacturing Excellence with Digital-Twin-Enabled Operational Monitoring and Intelligent Scheduling

This research examines the potential of digital twin (DT) technology for reformation within China’s traditional solid-wood-panel processing industry, which currently suffers from production inefficiencies and the slow adoption of digital technology. The research centers around developing a digital twin system, elucidating improvements in manufacturing efficiency, waste management, process simulation, and real-time monitoring. These capabilities facilitate immediate problem solving and offer transparency in the process. The digital twin system is comprised of physical, transport, virtual, and application layers, employing a MySQL database and using the Open Platform Communications Unified Architecture (OPC UA) protocol for communication. The application of this system has led to heightened production efficiency and better material use in the solid-wood-panel manufacturing line. Integrating the dynamic selection adaptive genetic algorithm (DSAGA) into the virtual layer drives the system’s efficiency forward. This evolved approach has allowed for an enhancement of 8.93% in the scheduling efficiency of DSAGA compared to traditional genetic algorithms (GAs), thereby contributing to increased system productivity. Real-time mapping and an advanced simulation interface have strengthened the system’s monitoring aspect. These additions enrich data visualization, leading to better comprehension and a holistic process view. This research has ignited improvements in solid-wood-panel production, illustrating the tangible benefits and representing progress in incorporating digital technology into traditional industries. This research sets a path for transforming these industries into smart manufacturing by effectively bridging the gap between physical production and digital monitoring. Furthermore, the adjustability of this approach extends beyond solid-wood-panel production, indicating the capability to expedite movement towards intelligent production in various other manufacturing sectors.

Fully Distributed Hierarchical ET Intrusion- and Fault-Tolerant Group Control for MASs With Application to Robotic Manipulators

This paper studies group synchronization tracking problem for a class of high-order multi-agent systems (MASs) with nonidentical and unknown direction faults (NUDFs) under multiple cyber attacks (i.e., denial-of-service (DoS) attacks and false data injection attacks (FDIAs)). Be motivated by this, a fully distributed hierarchical (cyber layer and physical layer) Zeno-free event-triggered (ET) intrusion-and fault-tolerant controller is presented based on Nussbaum-type gain technique, where a positive inter-event time exists in the state-dependent asynchronous ET mechanism (ETM). The constructed virtual cyber layer realizes the interaction among different agents so as to avoid the interaction in physical processes and thus reduce the error propagation. This two layer controller greatly increase the flexibility of the controller design compared with single-layer control strategies. In addition, a novel Nussbaum function stability lemma (Lemma lem4lem4) is developed for the first time. Based on this lemma, the fully distributed adaptive controller can adjust the direction of the input to match the fault direction with the help of Nussbaum function. Finally, a robotic manipulator example demonstrates the effectiveness and merit of the proposed control scheme. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In industrial processes, NUDFs and cyber attacks often occur in many different systems, which usually lead to performance degradation or even serious accidents. Typically, NUDFs affect the performance of chemical and industrial processes, circuits, and sensors. Meanwhile, in driverless vehicle platoon, attackers change the control signal through the wireless network, and then issue emergency braking commands, etc. Therefore, this paper designs a fully distributed hierarchical ET intrusion-and fault-tolerant scheme for high-order MASs that are usually used to model ship dynamics, robotic manipulators, and quarter-car active suspension. The control scheme gives solutions to the problem of NUDFs, multiple cyber attacks, and network bandwidth limitations at different layers, and effectively integrates the physical and cyber layers to achieve group synchronization. Meanwhile, a new event-triggered mechanism under the framework of group synchronization is developed to save communication resources. Robotic manipulator simulation studies verify the validity of the proposed scheme.

HClave: An isolated execution environment design for hypervisor runtime security

Virtualization is the cornerstone of cloud computing, but the hypervisor, the crucial software component that enables virtualization, is known to suffer from various attacks. It is challenging to secure the hypervisor due to at least two reasons. On one hand, commercial hypervisors are usually integrated into a privileged Operating System (OS), which brings in a larger attack surface. On the other hand, multiple Virtual Machines (VM) share a single hypervisor, thus a malicious VM could leverage the hypervisor as a bridge to launch “cross-VM” attacks. In this work, we propose HClave, an isolated execution environment (IEE) design for hypervisor runtime. We decouple the virtualization layer into a tiny trusted computing base (TCB), a large non-secure OS, and multiple HClave IEEs through a bidirectional isolation approach. HClave extends the nested kernel approach to deprive the traditional OS from accessing the tiny TCB’s memory and creates an IEE for hypervisor runtime. We implemented HClave based on KVM and evaluated its effectiveness and efficiency through case studies. Experimental results show that HClave can significantly improve the security of the hypervisor with reasonable runtime overhead.

A lubrication contact stiffness model considering asperity interactions

In practical engineering applications, most connection interfaces require lubrication. The contact stiffness of the lubrication interface can affect the static and dynamic characteristics of the interface, thus affecting the performance of the mechanical system, such as vibration, fatigue, and wear characteristics. Therefore, the measurement of lubrication contact stiffness is very important for the analysis and optimization of mechanical system performance. However, measuring the stiffness of the lubrication interface is a significant challenge. In this paper, a mixed lubrication contact stiffness model considering asperity interactions is proposed, which assumes the lubrication rough interface as an equivalent thin layer. The proposed model was compared with the lubrication contact model that does not consider the asperity interactions. Based on the microscopic contact behavior of the contact interface, the relationship between the mechanical parameters of the virtual thin layer and the contact pressure was analyzed. Finally, the predicted results of interface stiffness are verified by published theoretical and experimental results. The results show that the proposed model can more reasonably describe the actual contact behavior of the rough lubrication interface and give the variation law of the mechanical parameters of the virtual thin layer.

Architectural Support for Sharing, Isolating and Virtualizing FPGA Resources

FPGAs are increasingly popular in cloud environments for their ability to offer on-demand acceleration and improved compute efficiency. Providers would like to increase utilization, by multiplexing customers on a single device, similar to how processing cores and memory are shared. Nonetheless, multi-tenancy still faces major architectural limitations including: (a) inefficient sharing of memory interfaces across hardware tasks (HT) exacerbated by technological limitations and peculiarities, (b) insufficient solutions for performance and data isolation and high quality of service, and (c) absent or simplistic allocation strategies to effectively distribute external FPGA memory across HT. This article presents a full-stack solution for enabling multi-tenancy on FPGAs. Specifically, our work proposes an intra-fpga virtualization layer to share FPGA interfaces and its resources across tenants. To achieve efficient inter-connectivity between virtual FPGAs (vFGPAs) and external interfaces, we employ a compact network-on-chip architecture to optimize resource utilization. Dedicated memory management units implement the concept of virtual memory in FPGAs, providing mechanisms to isolate the address space and enable memory protection. We also introduce a memory segmentation scheme to effectively allocate FPGA address space and enhance isolation through hardware-software support, while preserving the efficacy of memory transactions. We assess our solution on an Alveo U250 Data Center FPGA Card, employing 10 real-world benchmarks from the Rodinia and Rosetta suites. Our framework preserves the performance of HT from a non-virtualized environment, while enhancing the device aggregate throughput through resource sharing; up to 3.96x in isolated and up to 2.31x in highly congested settings, where an external interface is shared across four vFPGAs. Finally, our work ensures high-quality of service, with HT achieving up to 0.95x of their native performance, even when resource sharing introduces interference from other accelerators.

Digital twin-assisted service function chaining in multi-domain computing power networks with multi-agent reinforcement learning

The emerging computing power network (CPN) is believed to undergo the paradigm reformation of network function virtualization (NFV) and service function chaining (SFC). It is prerequisite to explore the performance upper bound of NFV-assisted CPN before truly deploying the NFV and SFC technologies onto physical networks. Inspired by the application of digital twin (DT) in the industry and due to its advantage in synchronizing physical objects with their virtual replicas, we propose to use the DT to assist the SFC deployment in the multi-domain CPN, with the aid of multi-agent deep deterministic policy gradient (MADDPG) framework. First, we build a dynamic SFC mapping problem in the virtual twin network layer, by modeling the computing power, link bandwidth, delay performance and the VNF ordering as DT objects and constraints, to jointly optimize the energy consumption, end-to-end delay and the VNF re-deploying cost. Then, the prioritized experience replay and re-parameterization trick-empowered centralized training and decentralized execution MADDPG framework is utilized to learn the SFC deployment, by taking each domain controller as one agent. Finally, numerical experiments are carried out to validate the effectiveness of MADDPG in the cross-domain SFC deployment. For performance verification, the deployment success rate, number of crossed domains, energy consumption, end-to-end latency and load balancing degree are all taken as metrics, to show the performance of MADDPG compared to other learning frameworks.

Virtuality engineering in esports

Traditional sports and esports benefit from the development of Information and Communications Technologies (ICT), including gaming, 4D image/video processing, augmented reality (AR), virtual reality (VR), machine learning (ML), artificial intelligence (AI), big data, high-performance computing (HPC), and cloud computing. On the fuzzy border between the areas of physical and modified reality, both types of sports can coexist. The hardware layer of esports includes PC, consoles, smartphones, and peripherals used to interface with computers, including sensors and feedback devices. The IT layer of esports includes algorithms required in the development of games, online platforms, and virtual reality. The esports community includes amateur and professional players, spectators, esports organizers, sponsors, and other stakeholders. Esports and gaming research spans throughout law (intellectual rights, insurance, safety, and age restrictions), administration (teams, clubs, organizations, league regulations, and tournaments) biology (medicine, psychology, addiction, training and education) Olympic and non- Olympic disciplines, ethical issues, game producers, finance, gambling, data acquisition and analysis. Our article aims to presents selected research issues of esports in the ICT virtualization layer.

An Ontology of Cyberspace as a Basis for Decision-making in Cyberoperations

In the cyberoperations community there is a commonly accepted starting point for describing cyberspace as comprising of multiple planes through which information flows. However, the model is not a tool that facilitates planning and executing cyberoperations. Tools do exist in the form of technical cybersecurity ontologies. At the moment the link between technical ontologies, that are the tools of experts, and the operational planning process is limited. These technical ontologies provide automated information that would support operational planning. At the moment cybersecurity experts translate the information that military professionals need, which may cause insufficiencies or distortions in communication or cause inconsistencies in the planning process. This paper presents the ongoing work of developing a model of cyberspace in the form of a core ontology. The ontology describes the flow of digital information between persons and the enabling technology as well as geographical data. It is intended as a tool that supports operational planning and decision-making in and through cyberspace, by enabling automation and reasoning. The model is created using the well-established Constructive Research Approach (CRA) methodology, and is developed on earlier research. CRA consists of six phases in which (1) the problem is defined, (2) an understanding of the topic is generated, (3) a solution (model) is constructed which then is (4) demonstrated. Then the models (5) theoretical connections are presented and the (6) scope of applicability is assessed. The challenges of developing an ontology of cyberspace as part of the third phase of the methodology are in focus. The ontology serves as an operational core ontology, aiming to link cybersecurity domain ontologies to the DOLCE+DnS Ultralite (DUL) foundational ontology. The ontology is based on research in Cyberspace Geography and Cyber Terrain. No earlier attempts at creating a core ontology of cyberspace grounded in a foundational ontology, based on these concepts, were found. Overall, the use of reference ontologies in cyberspace research is scarce and few are grounded in a foundational ontology. The starting point for the ontology is a model of cyberspace comprising of six layers, which are the 1) geographic layer, 2) physical network layer, 3) logical network layer, 4) socio-organizational layer, 5) virtual persona layer and finally the 6) persona layer. The model was complemented with levels describing action and information and partially excluded the outer levels 1 and 6, which were directly linked to the DUL foundational ontology.

Implementing Internet of Things Service Platforms with Network Function Virtualization Serverless Technologies

The need for adaptivity and scalability in telecommunication systems has led to the introduction of a software-based approach to networking, in which network functions are virtualized and implemented in software modules, based on network function virtualization (NFV) technologies. The growing demand for low latency, efficiency, flexibility and security has placed some limitations on the adoption of these technologies, due to some problems of traditional virtualization solutions. However, the introduction of lightweight virtualization approaches is paving the way for new and better infrastructures for implementing network functions. This article discusses these new virtualization solutions and shows a proposal, based on serverless computing, that uses them to implement container-based virtualized network functions for the delivery of advanced Internet of Things (IoT) services. It includes open source software components to implement both the virtualization layer, implemented through Firecracker, and the runtime environment, based on Kata containers. A set of experiments shows that the proposed approach is fast, in order to boost new network functions, and more efficient than some baseline solutions, with minimal resource footprint. Therefore, it is an excellent candidate to implement NFV functions in the edge deployment of serverless services for the IoT.

The interaction of information diffusion and epidemic transmission in time-varying multiplex networks with simplicial complexes and asymmetric activity levels

Information diffusion among individuals occurs in various ways, mainly involving pairwise and higher-order interactions, and their coexistence can be characterized by simplicial complexes. This paper introduces a novel two-layer model that investigates coupled information-epidemic propagation. Specifically, the upper layer represents the virtual layer that depicts information diffusion, where the interaction process among individuals is not only limited to pairwise interactions but also influenced by higher-order interactions. The lower layer denotes the physical contact layer to portray epidemic transmission, where the interaction process among individuals is only considered in pairwise interactions. In particular, the emergence of asymmetric activity levels in two-layer networks reshapes the propagation mechanism. We then employ the micro-Marko chain approach (MMCA) to establish the probabilistic transfer equation for each state, deduce the epidemic outbreak threshold, and investigate the equilibrium and stability of the proposed model. Furthermore, we perform extensive Monte Carlo (MC) simulations to validate the theoretical predictions. The results demonstrate that the higher-order interaction generates synergistic reinforcement mechanisms that both facilitate information diffusion and inhibit epidemic transmission. Moreover, this study suggests that the activity level of individuals at the physical contact level has a greater impact on epidemic transmission. In addition, we utilize two different networks to explore the influence of network structural features on the transmission and scale of epidemics.

Explainable AI for time series via Virtual Inspection Layers

The field of eXplainable Artificial Intelligence (XAI) has witnessed significant advancements in recent years. However, the majority of progress has been concentrated in the domains of computer vision and natural language processing. For time series data, where the input itself is often not interpretable, dedicated XAI research is scarce. In this work, we put forward a virtual inspection layer for transforming the time series to an interpretable representation and allows to propagate relevance attributions to this representation via local XAI methods. In this way, we extend the applicability of XAI methods to domains (e.g. speech) where the input is only interpretable after a transformation. In this work, we focus on the Fourier Transform which, is prominently applied in the preprocessing of time series, with Layer-wise Relevance Propagation (LRP) and refer to our method as DFT-LRP. We demonstrate the usefulness of DFT-LRP in various time series classification settings like audio and medical data. We showcase how DFT-LRP reveals differences in the classification strategies of models trained in different domains (e.g., time vs. frequency domain) or helps to discover how models act on spurious correlations in the data.