Proteins are complex biological information granules that play a crucial role in various cellular processes within living organisms. Processing 3D protein structures, which are the most informative from the biological point of view, is both intricate and time-consuming. In particular, performing 3D protein structure searches against large protein datasets involves identifying similarities and conducting structural alignments across numerous molecules (granules). This task demands advanced methods for matching identical and similar regions within protein structures and substantial computational resources to handle large collections of macromolecular data efficiently. In this paper, we present our parallel implementation of scalable 3D structural alignment on the Apache Spark big data platform. We describe a customized approach that leverages Spark data transformations within the data processing pipeline for the alignment process. Our experimental results demonstrate that this solution, tightly integrated with the Spark processing model, is both efficient and scalable, even with the increasing volume of protein structure data.

Automated Guided Vehicles are mobile robots de-signed for transportation purposes, and one of the most important problems associated with intelligent logistics is the problem of job scheduling. The goal is to find the optimal allocation of job execution by the number of available devices. The problem can be resolved with a simulation in which the different scenarios are evaluated. However, creating such a simulation model requires a statistical description of the problem. In this paper, we implement the simulation model for the AGV environment. Based on the mathematical description of the model, the discrete event simulation is created using the Python programming language and the SimPy library. We use the simulation to compare the solution of the job scheduling problem using the simulated annealing and genetic algorithms.

The rapid evolution of smart manufacturing and the pivotal role of Automated Guided Vehicles (AGVs) in enhancing operational efficiency, underscore the necessity for robust anomaly detection mechanisms. This paper presents a comprehensive approach to detecting anomalies based on AGV telemetry data, leveraging the potential of machine learning (ML) algorithms to analyze complex data streams and time series signals. By focusing on the unique challenges posed by real-world AGV environments, we propose a methodology that integrates data collection, preprocessing, and the application of specific AI/ML models to accurately identify deviations from normal operations. Our approach is validated through extensive experiments on datasets featuring anomalies caused by mechanical wear or excessive friction and issues related to tire and wheel damage, employing LSTM and GRU networks, alongside traditional classifiers like K-nearest neighbors and SVM. The results demonstrate the efficacy of our method in forecasting momentary power consumption as an indicator of mechanical anomalies, and in classifying wheel-related issues with high accuracy. This work not only contributes to the enhancement of predictive maintenance strategies but also provides valuable insights for the development of more resilient and efficient AGV systems in smart manufacturing environments.

A study of the smart grid cyber-physical system functioning was conducted and a behavioral model of its functioning was proposed. The concept of the object, event and state of the cyber-physical system was formalized at the basis of the proposed set-theoretical model, which made it possible to reflect the trajectories of the system's functioning and the behavior of both individual objects and the cyber-physical system as a whole on their basis. The proposed model is the basis for the formalization and analysis of the impact of cyberattacks of various kinds on objects in the cyber-physical system and their trajectories. A formalization of the impact of Man-in-the-Middle cyberattacks on the control level of the cyber-physical system of a smart grid, in which the attacker is considered as a part of the system itself, is proposed. The proposed formalization of the impact of MitM cyberattacks on cyberphysical systems will allow describing known cyberattacks and forming parameterized procedures for their detection, which can be considered as complex features for detection.

The work presents a data collection system from the RPL routing protocol for detecting distributed denial-of-service attacks in Internet of Things (IoT) networks operating on the basis of the 6LoWPAN and RPL protocols. The system consists of three modules: a data gathering module, a classification module and a detection module. The main feature of the data collection module was that data collection was provided by several sniffers installed in the network and with subsequent aggregation of the collected data. For the implementation of the classification module, research was carried out on the method of support vector machines (SVM) and a multilayer perceptron (MLP). The detection module was used to broadcast a message about the abnormal behavior to the rest of the IoT network nodes, containing the ID of the compromised node and the path to it. To evaluate the efficiency of the proposed system that is based on the data collected by the data gathering module, a number of experiments were conducted. To obtain the data set for the experiments, an infrastructure based on the Ubuntu operating system and the Cooja simulator was deployed, which allowed to simulate the RPL network. Based on the operation of the deployed network, network traffic was collected that corresponded to both legitimate traffic and traffic during a black hole attack. The total number of test data was 24,023 samples. According to the research results, it was established that the SVM-based model demonstrated better performance level, in particular, the accuracy of detecting denial-of-service attacks was 89.6%, while the rate of false positives was 6%.

Data exchange in the multimedia system between the camera and the computer can be realized via the USB communication interface. Applying the USB port requires tuning the port parameters in such systems to ensure the quality of the services (multimedia) provided. The tuning of the communication system depends on such selection of port parameters to optimize the imposed criteria. The authors proposed a quality criterion based on the USB isochronous interval. The paper briefly presents the quality measure and the transmission model of the data package. Next, the problem of tuning the USB port was presented based on the selected parameters (MaxPacketSize and MaxBurst) of the endpoint of the peripheral device. To assess the impact of the selected parameter on the quality of services in the system, a statistical test for homoscedasticity of empirical distributions of isochronous intervals, was used. Besides the results of the conducted experiments for the selected parameters presented in the paper, the authors also tried to explain the obtained results in relation to the specification of the USB port.

On one bus IEEE 1394A may be a lot of protocols (eg. IIDC and SBP-2) that interact. On this bus cycle jitter may occur, which is not desired in A/V systems. This paper presents a method for measuring isochronous cycle duration. This method allows detection of cycle jitter. It is based on dedicated IEEE 1394 Device Driver and do not require reorganization of a topology of communication system. This article presents the results of measurement of cycle duration in communication system under test.

Industrial real-time computer systems are designed to operate with high reliability level. It is most often achieved by the use of redundancy. Additional elements introduced to the system are supposed to make it invulnerable to failures of their redundant components. Implementation of redundancy entails significant extra costs. The financial costs are quite obvious and easy to estimate they are associated with the need to deliver, configure, program, service and maintain additional devices and communication interfaces. There are however another costs which are not so evident because they derive from the system operation and data processing. Those are the temporal costs of redundancy that influence the real-time systems characteristics and in the end may determine the system usability.

Redundancy is the main method for achieving high reliability level in networked control systems NCSs. It is often applied in network interfaces in order to maintain operability of communication subsystems even when faults occur. In most cases, redundant communication buses realize exactly the same functionality as the initial non-redundant bus. That makes the system more reliable but the additional throughput of the redundant buses is not exploited even if the system condition would allow it. The idea of taking advantage of that throughput had made the authors to work on multi-network interface node which on the other hand maintain the high reliability of the communication subsystem, and on the other, makes it possible to manage the additional communication resources more efficiently, and therefore increases some parameters of the communication network.

USB 3.1 is the newest version of the ubiquitous Universal Serial Bus. It is used in various applications such as A/V system, where USB connects a few video cameras to one computer. In this case, quality of service depends not only on task scheduling or computer networks but also on communication interfaces (I/O subsystem). The newest version of USB improves communication efficiency by introducing some new mechanisms such as full-duplex transmission, burst transactions, etc. Thus verification of USB compliance with QoS is an important issue and this article presents a proposal of downstream and upstream scheduling process model. Furthermore, results of QoS guarantee tests have been depicted in three-dimensional Cartesian coordinate system.

The paper refers to the time parameters of transmission in industrial systems that use two buses. Applying the systems with two buses makes sense only if it is possible to control the transmission all the time, and make modifications and reconstruction of transmission scenario in case of a failure. The paper presents the results of empiric research into testing software algorithm for failure detection of transmission line and network node in industrial communication system. After implemented this algorithm in PLC the results referring to measurements of duration of basic transaction in a system and duration of failure detection on communication buses were presented. The authors tried to clarify whether a failure detection in two buses transmission can have an influence on the delays of transmission. The paper consists of description of a test bench for time parameters measurements, the test results and conclusion.

Real-Time services over IP (RTIP) have been increasingly significant due to the convergence of data networks worldwide around the IP standard, and the popularisation of the Internet. Real-Time applications have strict Quality of Service (QoS) constraint, which poses a major challenge to IP networks. The Cognitive Packet Network (CPN) has been designed as a QoS-driven protocol that addresses user-oriented QoS demands by adaptively routing packets based on online sensing and measurement, and in this paper we design and experimentally evaluate the“Real-Time (RT) over CPN” protocol which uses QoS goals that match the needs of real-time packet delivery in the presence of other background traffic under varied traffic conditions. The resulting design is evaluated via measurements of packet delay, delay variation (jitter) and packet loss ratio.

Designing systems with parallel transmission for industrial purposes, requires first defining the types of a failure, and next detecting it. Another step is to execute an appropriate procedure that can ensure the continuity of transmission. The issue of a failure detection can be a problem in itself, but is can also be a component of data transmission via dual bus. To make the transmission system work correctly, apart from creating the scenario of exchanges, it is necessary to solve the problem of a failure occurrence so that to maintain the transmission continuity. The paper presents the methods of failure detection and algorithms used when such failure occurs.

This book constitutes the thoroughly refereed proceedings of the 22st International Conference on Computer Networks, CN 2015, held in Brunw, Poland, in June 2015. The 42 revised full papers presented were carefully reviewed and selected from 79 submissions. The papers in these proceedings cover the following topics: computer networks, distributed computer systems, communications and teleinformatics.

The paper presents the theoretical and empirical tests which examine the algorithms of automatic scenario selection of cyclic exchange in transmission via two buses. The implemented method is the base for using the second (redundant) bus for data transmission. The main aim of this method is to build two-stream data transmission so that each data stream has similar, or even the same transmission time. The flexibility of the proposed solution results from the fact that it is useful not only for two-bus transmission, but also when the transmission is via only one bus. This method allows estimating the time of the network cycle and also indicates the values of the times for acyclic transmissions. The presented method is only the introduction to designing, developing and controlling the two-stream transmission.

The Internet transports data generated by programs which cause various phenomena in IP flows. By means of machine learning techniques, we can automatically discern between flows generated by different traffic sources and gain a more informed view of the Internet. In this paper, we optimize Waterfall, a promising architecture for cascade traffic classification. We present a new heuristic approach to optimal design of cascade classifiers. On the example of Waterfall, we show how to determine the order of modules in a cascade so that the classification speed is maximized, while keeping the number of errors and unlabeled flows at minimum. We validate our method experimentally on 4 real traffic datasets, showing significant improvements over random cascades.

The newest versions of the most ubiquitous USB interface are 3.0/3.1. USB 3.0 improves utilization of bus throughput through the changing of system architecture and introduction a new scheduling algorithm. In some applications using USB ports (e.g. vision system), the quality of service (QoS) is required. This paper presents proposal of model of USB system based on theory of scheduling and definition of QoS for communication interfaces (in particular USB 3.0). Some experiments (using prepared USB 3.0 application) were performed to verify compliance with QoS and their results are shown in this article.

The main objective of the paper was to test whether the devices compatible with Bluetooth Low Energy are reliable for indoor localization system. To determine the reliability of this technology several tests were performed to check if measured distance between Bluetooth transmitter and mobile device is close to the real value. Distance measurement focused on Bluetooth technology based mainly on received signal strength indicator (RSSI), which is used to calculate the distance between a transmitter and a receiver. As the research results show, the Bluetooth LE signal power cannot be the only reliable source of information for precise indoor localization.