Infrastructure Nodes Research Articles

ПОДХОД К АНАЛИЗУ СОСТОЯНИЯ УЗЛОВ «ИНДУСТРИИ 4.0» НА ОСНОВЕ ПОВЕДЕНЧЕСКИХ ПАТТЕРНОВ

The imperfection of systems for monitoring and analysing the state of hard-to-reach devices and nodes, dynamically flowing technological processes associated with them necessitates the analysis of not only “internal” data, but also those arriving through external and external channels. This article discusses one of the most effective ways to solve this problem by using digitized data sequences grouped into behavioural patterns. The analysed device, as a rule, is outside the controlled area, and access to it is limited, as a result, all processes occurring inside the devices must be under constant control. Changes in temperature, amplitude and frequency of vibrations, sound, and electromagnetic spectra taken by sensors and sensors during the production and operation of individual components may indicate the need for changes in the technological process in order to prevent wear, breakdowns, and rejects. Thus, the analysis of the state of hard-to-reach nodes and devices of Industry 4.0 based on incoming data from external side channels is an urgent task. The essence of the proposed approach is to obtain the dependence of the quantitative indicators of the functioning of devices, infrastructure nodes of "Industry 4.0" for various modes of operation and further use of the obtained data when solving the problem of analysing the state of devices and infrastructure nodes of "Industry 4.0". The novelty of this study is the development of an approach to the analysis of Industry 4.0 devices designed to identify the state of remote and hard-to-reach devices, which combines machine-learning technologies in the analysis of heterogeneous external data of digitized trac es of signal sequences coming from various elements and combined into behavioural patterns.

Resilient Service Chains through Smart Replication

The Internet of Things paradigm enables a new set of smart end-user applications. The Cloud-Fog-Mist-Internet of Things infrastructure provides communication, compute, and storage support for these applications. However, this complex, heterogeneous, and distributed landscape requires orchestration and management mechanisms in order to guarantee their proper functioning. One particular factor to manage is the capacity to provide service resilience even in the presence of failures in components of the substrate infrastructure. This research proposes a set of mechanisms to formalize, orchestrate, and embed a batch of service requests for chained Virtual Functions to fulfill the specific requirements of applications while enhancing their availability and ultimately their resilience. In detail, this work introduces a formal grammar to describe customized Service Chains, allowing the definition of replicas for different Virtual Functions, and an Integer Linear Programming model for Virtual Function embedding that prioritizes the use of nodes with higher availability. Additionally, an alternative heuristic is presented to handle more complex scenarios by taking advantage of the multi-tier scenario comprising the Cloud-Fog-Mist-Internet of Things. Simulation results for the embedding mechanisms show that it is possible to increase the resilience of chained Virtual Functions, while balancing the load of the infrastructure nodes.

ODPV: An Efficient Protocol to Mitigate Data Integrity Attacks in Intelligent Transport Systems

Intelligent Transport Systems (ITS) require accurate information to be shared among vehicles and infrastructure nodes for applications including accident information or pre-crash warnings, to name a few. Due to its sensitive nature, ITS applications are vulnerable against data integrity attacks where nodes transmit false information that results in wrong decision making by the applications. A characteristic of such attacks is that the false transmitted information is significantly different than the actual information. In this paper, we propose an Outlier Detection, Prioritization and Verification (ODPV) protocol that efficiently isolates false data and improves traffic management decisions. ODPV uses the isolation forest algorithm to detect outliers, fuzzy logic to prioritize outliers and C-V2X communications to verify the outliers. Extensive simulation results verify the effectiveness of the proposed protocol to isolate the outliers.

Coverage in One-Dimensional Wireless Networks With Infrastructure Nodes and Relay Extensions

We consider a wireless network comprising two types of nodes, namely, sinks and relays. The sink nodes are connected to a wireline infrastructure, while the relay nodes are used to extend the region covered by providing multi-hop paths to the sink nodes. Restricting to the one-dimensional setting, our objective is to characterize the fraction of covered region as a function of sink and relay node densities. We first compare and contrast our infrastructure-based model with the traditional setting where every node is a sink, and hence a location is covered if it simply lies within the range of some node. Then, drawing an analogy between the connected components of the network and the busy periods of an M/D/∞ queue (and using renewal theoretic arguments) we derive a closed-form expression for the average vacancy (complement of coverage). We also compute an upper bound for vacancy by introducing the notion of left-coverage (i.e., coverage by a node on the left); a lower bound is derived by coupling our model with an independent-disk model, where the sinks' coverage regions are independent and identically distributed. Through an extensive theoretical and numerical study, we investigate the problem of minimizing network deployment cost subject to a constraint on the average vacancy. We also conduct simulations to understand the properties of a general notion of coverage, obtained by introducing hop-counts into the definition. Parameterized approximations for the hop-constrained cluster lengths (around a sink) are proposed, whose efficacy is evaluated numerically. In particular, there exists a range of parameter values where our cluster-length approximation is good. Finally, hop-constrained cost optimization is conducted to demonstrate the efficacy of the infrastructure-based design.

Experimental Evaluation of a UWB-Based Cooperative Positioning System for Pedestrians in GNSS-Denied Environment.

Cooperative positioning (CP) utilises information sharing among multiple nodes to enable positioning in Global Navigation Satellite System (GNSS)-denied environments. This paper reports the performance of a CP system for pedestrians using Ultra-Wide Band (UWB) technology in GNSS-denied environments. This data set was collected as part of a benchmarking measurement campaign carried out at the Ohio State University in October 2017. Pedestrians were equipped with a variety of sensors, including two different UWB systems, on a specially designed helmet serving as a mobile multi-sensor platform for CP. Different users were walking in stop-and-go mode along trajectories with predefined checkpoints and under various challenging environments. In the developed CP network, both Peer-to-Infrastructure (P2I) and Peer-to-Peer (P2P) measurements are used for positioning of the pedestrians. It is realised that the proposed system can achieve decimetre-level accuracies (on average, around 20 cm) in the complete absence of GNSS signals, provided that the measurements from infrastructure nodes are available and the network geometry is good. In the absence of these good conditions, the results show that the average accuracy degrades to meter level. Further, it is experimentally demonstrated that inclusion of P2P cooperative range observations further enhances the positioning accuracy and, in extreme cases when only one infrastructure measurement is available, P2P CP may reduce positioning errors by up to . The complete test setup, the methodology for development, and data collection are discussed in this paper. In the next version of this system, additional observations such as the Wi-Fi, camera, and other signals of opportunity will be included.

Adaptive proportional fair scheduling with global-fairness

In practical communication systems, there are always multiple subscribers competing for limited resources, such as time and frequency, hence effective user scheduling is essential to multi-user communications in achieving good system throughput and fairness performance. The conventional proportional fair (PF) scheduling achieves fairness at the cost of system spectral efficiency (SE) loss. Such fairness is of long-term feature, i.e., all the users’ scheduling probabilities become approximately the same only when the observation time is long enough. Therefore, PF cannot guarantee the fairness for subscribers who enter the system temporarily or stay in the system for a short period of time. In addition, delay requirement of real-time-service users can hardly be met with conventional PF. In order to remedy these deficiencies, we propose adaptive proportional fair (APF) scheduling algorithms. In each time slot, the infrastructure node, e.g., base station, dynamically adjusts the forgetting factor based on the variance of all the subscribers’ scheduling priorities, so that users’ scheduling weights can be adaptively updated. Our in-depth simulation results show that compared to conventional PF, APF can not only achieve both long-term and short-term fairness which we refer to global-fairness, but also obtain high system SE. Moreover, users’ delay performance can be obviously improved.

The village as urban infrastructure: Social reproduction, agrarian repair and uneven urbanisation

This paper draws from research conducted in Gurgaon, a city which has been transformed from agricultural hinterland to a bustling metropolis over the course of the past 30 years. The aim of this paper is to expand debates on the uneven geographies of urbanisation in India by reconsidering marginalised urban neighbourhoods as infrastructural nodes, wherein the complex and contested work of reproducing urban life is carried out. Extending scholarship on urban infrastructure, social reproduction and heterodox Marxist political economy, this paper highlights the subaltern processes decay and repair which underpin Gurgaon’s rapid urbanisation.

TOPSIS METODO PRITAIKOMUMAS ŠALIES YPATINGOS SVARBOS INFRASTRUKTŪROS OBJEKTAMS / THE APPLICATION OF TOPSIS METHODOLOGY FOR IDENTIFICATION OF NATIONAL CRITICAL INFRASTRUCTURE

Various countries apply different methodology for national critical infrastructure identification. MCDM method TOPSIS is extensively used in different areas of research such as logistics, health. The best alternative is based on all criteria, dependant on their significance. The paper presents the study of multi-ple criteria decision-making method TOPSIS application for identification of Lithuanian national critical infrastructure. The experiments demonstrate, that use of MCDM ensure better and more stable identification of critical infrastructure resulting in concentrating protection efforts and resources on the most important infrastructure nodes.

Application Component Placement in NFV-Based Hybrid Cloud/Fog Systems With Mobile Fog Nodes

Fog computing reduces the latency induced by distant clouds by enabling the deployment of some application components at the edge of the network, on fog nodes, while keeping others in the cloud. Application components can be implemented as Virtual Network Functions (VNFs) and their execution sequences can be modeled by a combination of sub-structures like sequence, parallel, selection, and loops. Efficient placement algorithms are required to map the application components onto the infrastructure nodes. Current solutions do not consider the mobility of fog nodes, a phenomenon which may happen in real systems. In this paper, we use the random waypoint mobility model for fog nodes to calculate the expected makespan and application execution cost. We then model the problem as an Integer Linear Programming (ILP) formulation which minimizes an aggregated weighted function of the makespan and cost. We propose a Tabu Search-based Component Placement (TSCP) algorithm to find sub-optimal placements. The results show that the proposed algorithm improves the makespan and the application execution cost.

City-campus, or Educational Space of the City. Methodological Construct

The article considers the city from the point of view of its educational potential and in the categories of educational space, approaching the main cultural and historical forms of the city as educational institutions. With this review, at least three focus points are retained: 1) Consideration of the city space and its infrastructure as an educational space and educational infrastructure that are not reducible to usual school and university (the latter should also be culturally and historically distributed, showing their basic etymons and missions); 2) Consideration of education as an institution of educational and, more broadly, anthropological practices of the development and formation of a person, and not as a disciplinary institution and matrix; 3) Consideration of the repertoire of anthropological practices development as a practice unfolding in urban space. It is shown that these three foci act as mirrors directed at each other, mirroring and showing each other mutual potential and mutual scarcity, the need for each other. The actual wealth (thesaurus) of the urban space depends on the density, frequency and variety of connections between these areas. Next, we look at specific cultural and historical forms, such as the Temple, School, Museum, University, etc., which constitute the basic infrastructure nodes of the city space itself. These cultural institutions are considered not so much from the point of view of their internal tasks, but from the position of their place in the city, in the urban space, with regard to their place and role as special educational nodes-institutions in this space. Further, the urban space is considered in the categories of the campus city, in which this space is linked by different anthropological practices repertoires.

Fog Computing-Assisted Trustworthy Forwarding Scheme in Mobile Internet of Things

The interaction between mobile Internet of Things (IoT) devices is based on a hybrid communication architecture. To improve packet delivery ratio, reduce end-to-end delay, and protect data privacy, designing an efficient data forwarding scheme is crucial in guaranteeing the quality of data transmission. Fog computing, a novel distributed computing framework, can decrease the amount of data transmission on the Internet and improve quality of services. In this paper, we propose a fog computing-assisted trustworthy forwarding (FCTF) scheme. To the best of our knowledge, this paper is the first study that investigates the role of fog infrastructure nodes (FINs) in forwarding scheme design. FCTF first selects the contact probability and the service degree as the basic trustworthy metrics between node pairs, and combines high-performance optimization algorithms to design a dynamic detection model of overlapping trustworthy communities (DOTCs). Then, we construct logical joint edge community structures on the basis of the results of DOTC and the distribution of FINs at each timestamp. Finally, based on the logical joint edge community, we define the forwarding utilities for FINs and mobile devices, respectively, and design self-adaptive forwarding rules. The experimental results prove that our FCTF scheme can enhance the delivery ratio, and decrease the latency and average hop-count more effectively, and has better routing quality compared with some popular forwarding models in mobile IoT applications.

UWB Localization with Battery-Powered Wireless Backbone for Drone-Based Inventory Management.

Current inventory-taking methods (counting stocks and checking correct placements) in large vertical warehouses are mostly manual, resulting in (i) large personnel costs, (ii) human errors and (iii) incidents due to working at large heights. To remedy this, the use of autonomous indoor drones has been proposed. However, these drones require accurate localization solutions that are easy to (temporarily) install at low costs in large warehouses. To this end, we designed a Ultra-Wideband (UWB) solution that uses infrastructure anchor nodes that do not require any wired backbone and can be battery powered. The resulting system has a theoretical update rate of up to 2892 Hz (assuming no hardware dependent delays). Moreover, the anchor nodes have an average current consumption of only 27 mA (compared to 130 mA of traditional UWB infrastructure nodes). Finally, the system has been experimentally validated and is available as open-source software.

Автоматизация обнаружения и анализа ошибок в гиперконвергентных системах

The paper is devoted to the problem of early error detection and analysis in hyperconverged systems. One approach to organizing hyperconverged systems is to install on each physical server a separate instance of an operating system (OS) that carries virtualization tools and tools for administering and using a distributed data warehouse. Errors can occur both at the level of a single OS instance and at the level of the entire cluster. For example, incorrect control element commands from one infrastructure node can cause software failure on another node. In addition, errors from the subsystems of the cluster can provoke abnormal situations inside virtual machines. The complexity of the architecture of hyperconverged systems makes it difficult to analyze the errors that occur in them. To simplify such an analysis and increase its effectiveness, it is necessary to automate the process of detecting problems and collecting data necessary for their study and correction. Existing approaches for automation of error detection are described and various improvements are suggested to adopt them for systems where distributed storage and virtualization technologies are actively used. Improvements include log collection from the whole cluster just after the error occurred, additional analysis of guest operating system behaviour inside virtual machines, usage of a knowledge base for automated crash recovery and duplicate detection. Finally, a real-life scenario of error handling process in Virtuozzo company products is described starting from error detection and ending with fix deployment.

60-GHz Millimeter-Wave Propagation Inside Bus: Measurement, Modeling, Simulation, and Performance Analysis

Millimeter-wave (mmWave) transmission over the unlicensed 60-GHz spectrum is a potential solution to realize high-speed internet access, even inside mass transit vehicles. The solution involves communication between users and a mmWave-band on-board unit that aggregates/disseminates data streams from/to commuters and maintains the connection with the nearest terrestrial network infrastructure node. In this paper, we provide a measurement-based channel model for the 60-GHz mmWave propagation inside a typical inter-city bus. The model characterizes power delay profile (PDP) of the wireless intra-vehicular channel, and it is derived from about 1000 data sets measured within the bus. The proposed analytical model is further translated into a simple simulation algorithm that generates in-vehicle channel PDPs. Different goodness-of-fit tests confirm that the simulated PDPs are in good agreement with the measured data. Finally, a tapped-delay-line (TDL) channel model is formulated from the proposed PDP model, and the TDL model is used to study the bit error rate (BER) performance of the mmWave link inside bus under varying data rates and link lengths.

On the Relationship Between Relay and Infrastructure Densities in Geometrically Bounded Relay-Assisted Wireless Networks

In this paper, we study the connectivity between two fixed terminal nodes within a geometrically bounded network of relay nodes and fixed infrastructure nodes. We assume that a communication path, between the terminal nodes, can be established by direct connection (1-hop), via a relay node (2-hop) or via the infrastructure network; the choice is based on link viability in a Rayleigh fading environment. We adopt a probabilistic approach to our analysis considering a homogeneous spatial distribution of relay nodes and an inhomogeneous spatial distribution of infrastructure nodes. Our analysis of the relationship between relay and infrastructure densities for a prescribed outage probability shows that reliance on infrastructure connectivity can be appreciably reduced by employing direct and 2-hop connectivity. We further show that, as the relay density increases, optimum connectivity is achieved by employing a non uniform spatial thinning of the infrastructure, which is dependent upon the geometric extent of the network. Our analysis provides an insight into multi-mode connectivity in bounded network domains and has application in many fields including cellular and vehicle-to-infrastructure (V2X), which are often modelled as having finite extent and where reducing the reliance on fixed infrastructure can effectively reduce operating expenditure costs.

A oneM2M-Based Query Engine for Internet of Things (IoT) Data Streams.

The new standard oneM2M (one machine-to-machine) aims to standardize the architecture and protocols of Internet of Things (IoT) middleware for better interoperability. Although the standard seems promising, it lacks several features for efficiently searching and retrieving IoT data which satisfy users’ intentions. In this paper, we design and develop a oneM2M-based query engine, called OMQ, that provides a real-time processing over IoT data streams. For this purpose, we define a query language which enables users to retrieve IoT data from data sources using JavaScript Object Notation (JSON). We also propose efficient query processing algorithms which utilizes the oneM2M architecture consisting of two nodes: (1) the IoT node and (2) the infrastructure node. IoT nodes of OMQ are mainly sensor devices execute user queries the aggregate, transform and filter operators, whereas the infrastructure node handles the join operator of user queries. Since the query processing algorithms are implemented as the hybrid infrastructure-edge processing, user queries can be executed efficiently in each IoT node rather than only in the infrastructure node. Thus, our OMQ system reduces the query processing time and the network bandwidth. We conducted a comprehensive evaluation of OMQ using a real and a synthetic data set. Experimental results demonstrate the feasibility and efficiency of OMQ system for executing queries and transferring data from each IoT node.

Toward a lightweight and efficient UAV‐aided VANET

AbstractConnectivity in a smart vehicular network is quite sensitive and highly affected by its dynamic network topology. Issues related to the intermittent nature of connectivity may arise due to the high mobility of nodes and network heterogeneity. In sparse areas, a vehicular network is basically a disruption‐tolerant network suffering from frequent disconnections, long delays, and messages loss. Facing these issues, and specifically for time‐sensitive applications, Unmanned Aerial Vehicle (UAV) can provide valuable assistance to Vehicular Ad Hoc Network (VANET) by assuming a relay node role between disconnected segments in the road. In such scenarios, effective communication is either between vehicles (V2V) or between vehicles and UAVs (V2U), which would form subsequently a UAV‐assisted vehicular network. In the present paper, we propose a new framework for using small UAVs as mobile infrastructure nodes in order to enhance the connectivity between vehicles. The first part of this framework accurately predicts the disconnected segments such that drones can be deployed to reestablish lost links. We have implemented a theoretical game for this prediction process. Furthermore, since the battery reserves of the UAVs are limited, we have proposed a mitigation technique based on game theory to reduce the power draining effects that a broadcast storm would have on the energy consumption of the network. For the validation of the proposed UVE (UAV‐aided VANET framework, with energy‐conscious constraints), we conducted thorough simulation scenarios with Network Simulator 3. The obtained performances are promising in the sense that our approach achieves high packet delivery ratio, low end‐to‐end delay, and low overhead communication costs.

Shared Rate Process for Mobile Users in Poisson Networks and Applications

This paper focuses on the modeling and analysis of the temporal performance variation experienced by a mobile user in a wireless network and its impact on system-level design. We consider a simple stochastic geometry model: the infrastructure nodes are Poisson distributed while the user’s motion is the simplest possible, i.e., constant velocity on a straight line. We first characterize variations in the signal-to-noise ratio (SNR) process and associated downlink Shannon rate, resulting from variations in the infrastructure geometry seen by the mobile. Specifically, by making a connection between stochastic geometry and queuing theory, the level crossings of the SNR process are shown to form an alternating renewal process whose distribution is completely characterized. For large/small SNR levels, and associated rare events, we further derive simple distributional (exponential) models. We then characterize the second major contributor to such variations, namely, changes in the number of other users sharing the infrastructure. Combining these two phenomena, we study what are the dominant factors (infrastructure geometry or sharing number) when a mobile experiences a very high/low shared rate. These results are then used to evaluate and optimize the system-level quality of experience of the mobile users sharing such a wireless infrastructure, including mobile devices streaming video which proactively buffer content to prevent rebuffering and mobiles which are downloading large files. Finally, we use simulation to assess the fidelity of this model and its robustness to factors which are presently not taken into account.

Mobility‐Centric Analysis of Communication Offloading for Heterogeneous Internet of Things Devices

Today, the number of interconnected Internet of Things (IoT) devices is growing tremendously followed by an increase in the density of cellular base stations. This trend has an adverse effect on the power efficiency of communication, since each new infrastructure node requires a significant amount of energy. Numerous enablers are already in place to offload the scarce cellular spectrum, thus allowing utilization of more energy‐efficient short‐range radio technologies for user content dissemination, such as moving relay stations and network‐assisted direct connectivity. In this work, we contribute a new mathematical framework aimed at analyzing the impact of network offloading on the probabilistic characteristics related to the quality of service and thus helping relieve the energy burden on infrastructure network deployments.

Security Provisioning for MISO Vehicular Relay Networks via Cooperative Jamming and Signal Superposition

We study the cooperative secure transmissions in (multiple-input signal-output) MISO vehicular relay networks where the infrastructure node with multiple antennas sends two confidential messages to two legitimate vehicles with only one antenna, respectively. By exploiting the signal superposition and cooperative jamming techniques, the legitimate vehicle near the infrastructure node directly decodes its own messages and is also responsible for relaying messages for the other legitimate vehicle who is distant from the infrastructure node. To combat eavesdropping threat from a malicious node for these two legitimate vehicles, we first provide comprehensive analysis of the secrecy performances and then design optimal secure transmission schemes for both vehicles. In particular, we first derive the closed-form expressions of the transmission outage probability (TOP) and secrecy outage probability (SOP), which offer mathematic tools for separate control with respect to security and system throughput. Following these results, we develop the optimized transmission schemes for two typical secure communication scenarios. One scenario is to maximally suppress the message leak while maintaining satisfied transmission rate. To achieve this goal, we derive the optimal power allocation strategy to minimize the SOP under the upper bounded TOP requirement. The other scenario is to improve the average secrecy rate with system throughput taken into consideration. Corresponding, we propose a prioritized and an explicitly parameterized power allocation schemes, which address the mutual impact across legitimate vehicles transmissions by different approaches. Numerical results are presented to validate the derived theory analytical results and show the performance superiority of the proposed schemes in terms of the average secrecy rate and the SOP performance.