Networked Automation Systems Research Articles

NETWORK PROGRAMMABILITY FOR NETWORK ISSUE USING PARAMIKO LIBRARY

In a company, information technology is needed, especially computer networks, to facilitate data communication. The management of a computer network, of course, requires good administration. The criteria for whether or not a network is good can be seen from the performance, reliability, and security indicators so that it will not cause network issues. Events such as server downs, data loss, lost connections, and undetected computers cause the organization's business performance to be disrupted. This study's purpose is to detect network issues with network programmability technology automatically. Paramiko library supports network automation systems and implements OSPF routing protocol in finding the shortest path to send network packets. This study uses the PPDIOO flow, namely prepare, plan, design, implement, operate, and optimize, because it is considered by the flow of making network detection tools. The results showed that the design and implementation of a small-scale network were successfully built by utilizing network programmability technology and the paramiko library, which helps detect network conditions at any time. This design has a dashboard, provisioning, assurance, and policy features that allow administrators to manage and monitor information on each network device. The network design is fitted with REST-API technology and security through a secure shell (ssh) from the Network Controller that can detect the device's connection conditions and the device's health and update the DNS configuration used. Network Issues that have been seen are devices being down, and the connection being lost. Future research can improve features for network troubleshooting when the connection is lost.

Adversarial Analysis of ML-Based Anomaly Detection in Multi-Layer Network Automation

The fast development of multi-layer packet-over-optical networks has made network monitoring and troubleshooting increasingly complicated. This has stimulated people to combine machine learning (ML) and software-defined networking (SDN) to realize multi-layer network automation. Despite its initial successes, the vulnerabilities of multi-layer network automation have not been fully explored. This work studies how to mislead the ML-based classifiers for anomaly detection. Specifically, we design two adversarial-sample-based attack schemes based on the white-box attack (WBA) and black-box attack (BBA) strategies, respectively, to eavesdrop and tamper legitimate telemetry data samples and generate adversarial samples adaptively, for disturbing ML-based classifiers and in turn misleading network automation to make incorrect decisions. Compared with WBA, BBA makes the attack scheme more practical by minimizing the dependency on pre-knowledge of the target ML-based classifiers. Considering different types of ML-based classifiers, we build a real-world packet-over-optical testbed and leverage the telemetry samples collected in it to demonstrate that our proposed BBA scheme can interact with the network quietly to train itself, generate well-crafted adversarial samples to tamper legitimate telemetry samples in the hard-to-detect way, and mislead ML-based classifiers in the network automation system to severely affect their performance on anomaly detection.

Entropy-Driven Adaptive INT and Its Applications in Network Automation of IP-Over-EONs

Recently, IP over elastic optical network (IP-over-EON) has become a promising architecture for metro and core networks. This work studies how to visualize both layers of an IP-over-EON in real time, at different granularities (<i>e.g.</i>, at flow-level, lightpath-level, and link-level), and with self-adaptivity. Specifically, we consider the multilayer application of in-band telemetry (INT) and propose entropy-driven adaptive INT (namely, EntropyINT). We introduce stateful processing to programmable data plane (PDP) switches for EntropyINT, such that they can make local decisions to determine whether and what type of telemetry data about the IP and EON layers should be encoded in each packet. The local decisions are designed to be based on the amount of information that can be conveyed by telemetry data to the network automation system. Meanwhile, we make EntropyINT cooperate with out-of-band monitoring, to detect and locate exceptions in the EON layer. Our proposal is implemented in a real-world testbed of IP-over-EON, to evaluate its assistance to network automation. Experimental results verify the effectiveness of our proposal, and indicate that the telemetry data collected by EntropyINT and out-of-band monitoring can better assist the machine learning in network automation, for status prediction and anomaly detection.

Enhancing Time Synchronization for Home Automation Systems

Clock synchronization techniques are in highly demand for smart home applications with the approach of the Internet of Things (IoT). The developing innovation of smart home applications built on the Internet of Things is generally constrained and scattered. Synchronization is the basic characteristic of the emerging field of IoT in smart home applications which is recommended for improving the acceptance and its use. For the clock synchronization between systems, Network Time Protocol (NTP) is used. But due to inconsistent routing and limited computing resources there can be the dominant source of error that limits time transfer uncertainty. This paper proposes an Elastic Timer Protocol for home automation system networks that performs better in terms of consumption of energy and time of convergence than other clock synchronization protocols. The proposed protocol improves the elasticity and efficiency of the network, resulting in a faster network convergence time. Furthermore, simulation results revealed that the proposed work has improved performance metrics and proved superior performance characteristics when compared to standard synchronization protocols.

Research on Quantitative Security Protection Technology of Distribution Automation Nodes based on Attack Tree

In order to improve the security of distribution automation system nodes and ensure the safe operation of distribution network, a quantitative security protection technology for distribution automation nodes based on attack tree is proposed. This paper analyzes the factors of node risk assessment of the distribution automation system, and through the evaluation and analysis of node vulnerabilities; it discovers the faulty nodes in the distribution automation system in advance. Based on the node vulnerability evaluation results of the distribution automation system, the risk of the distribution automation system is comprehensively evaluated using the attack tree. Establish the distribution network control model under network attack, locate the fault node, and use trusted computing technology to design trusted distribution terminals. When the amount of data is large, more effective symmetric encryption algorithm SM4 is required to achieve node security protection in the distribution network automation system. The experimental results show that the method has high fault node location accuracy, low reliability calculation time, and the distribution automation system network has certain robustness, which fully verifies the application effect of the method.

Research on Key Technologies of Power System Automation in Smart Grid

The paper summarizes the construction mode of distribution network automation system, and sorts out the operating characteristics of centralized intelligent mode and distributed intelligent mode. In view of the construction and operation of China’s distribution network automation system, point out common problems in system construction, operation and management in most regions. At the same time, the paper proposes the optimization of distribution network automation technology based on the gravity search algorithm, and improves the algorithm. Finally, the improved gravity search algorithm is applied to the IEEE 6-node power system. The calculation results show that the active power loss and voltage obtained by the algorithm are Compared with the original state, the level has been greatly improved, which greatly improves the automation efficiency of the power system. In this paper, the gravity search algorithm is used to calculate the optimization of power system automation technology, and the algorithm is improved, which overcomes the shortcoming of easy convergence to the local optimum.

As-RaD System as a Design Model of the Network Automation Configuration System Based on the REST-API and Django Framework

The use of information technology these days are very high. From business through education activities tend to use this technology most of the time. Information technology uses computer networks for integration and management data. To avoid business problems, the number of network devices installed requires a manageable network configuration for easier maintenance. Traditionally, each of network devices has to be manually configured by network administrators. This process takes time and inefficient. Network automation methods exist to overcome the repetitive process. Design model uses a web-based application for maintenance and automates networking tasks. In this research, the network automation system implemented and built a controller application that used REST API (Representational State Transfer Application Programming Interface) architecture and built by Django framework with Python programming language. The design modeled namely As-RaD System. The network devices used in this research are Cisco CSR1000V because it supports REST API communication to manage its network configuration and could be placed on the server either. The As-RaD System provides 75% faster performance than Paramiko and 92% than NAPALM.

Highly-Efficient and Automatic Spectrum Inspection Based on AutoEncoder and Semi-Supervised Learning for Anomaly Detection in EONs

To closely monitor the performance of lightpaths in an elastic optical network (EON), people need to rely on real-time and fine-grained spectrum monitoring. This, however, will generate tremendous telemetry data, which can put great pressure on both the control and data planes. In this work, we design and experimentally demonstrate AutoSpecheck, which is a DL-assisted network automation (DLaNA) system that can realize highly-efficient and automatic spectrum inspection for anomaly detection in EONs. Specifically, we architect AutoSpecheck based on the software-defined EON (SD-EON) architecture, and propose techniques to greatly reduce the loads of data reporting (in the data plane) and data analyzing (in the control plane). To reduce the loads of data reporting, we leverage the AutoEncoder (AE) technique to design a spectrum data compression method. To improve the efficiency of data analytics, we first design a coarse filtering module (CFM) to let the control plane filter out most of the normal data before invoking the DL-based anomaly detection. Then, to address the difficulty of labeling massive spectrum data, we develop a DL-based anomaly detection based on semi-supervised learning. Our experimental demonstrations consider two representative intra-channel anomalies ( i.e. , the filter drifting and in-band jamming), and the results confirm that AutoSpecheck can achieve highly-efficient and automatic spectrum inspection for anomaly detection in EONs.

Response time evaluation of industrial-scale distributed control systems by discrete event systems formalisms

This research deals with the temporal performance analysis of distributed networked automation systems. It describes a new formal approach that estimates the maximum limit of response time in Networked Control Systems (NCS) that use a producer/consumer protocol. Two different tools of discrete event systems have been used: Timed Event Graphs (TEGs) and (Max,+) algebra. First, the contribution is to model all components of NCS with TEGs, and to represent the behaviour of these graphs by (Max,+) linear equations, and then to determine the upper bounds of the response time by an analytical formula. The main novelty of these results is to introduce a modular method capable of providing crucial validation elements regarding temporal performances for an industrial scale NCS that includes inter CPU communication. Moreover, the modular aspect of the presented approach remains in considering the end-to-end delays introduced by the network as model parameters, calculated from other models.

Research and implementation of information security for intelligent distribution network

The intelligent distribution network is an important hub for connecting power generation and users, and the security of its information is closely related to the stable operation of the power grid. In order to solve the contradiction between the security and real-time of information in intelligent distribution network according to Supplementary Provisions for Safety Protection of Medium and Low Voltage Distribution Network Automation System, an information security model of intelligent distribution network is proposed, after deeply studying AES encryption algorithm and SHA-256 authentication algorithm, using OPNET as simulation software for smart distribution network information to carryout transmission delay curve. FPGA is used as information security processing platform. We obtain the total delay, analyze the integrity and availability. The experiment proves that the intelligent distribution network information security processing solution satisfies the three elements of CIA information security, and has good confidentiality, integrity and availability.

配网自动化系统在胜利油田区域电网的应用与实践

配网自动化系统在胜利油田区域电网的应用与实践

A Physical Probabilistic Network Model for Distribution Network Topology Recognition Using Smart Meter Data

Given the considerable scale of distribution networks in urban and rural areas, as well as the lack of management records, adjustments of switches during the distribution system operation are poorly documented. Such deficiency results in the inaccuracy of models stored in the distribution network automation system, and thus misleads the state estimation. With the emergence of information and communication technology, a large number of the feeder and residential smart meter data are accumulated. Such data can help recognize the operation modes of distribution networks by analyzing the relationships between the on/off states of switches and the voltage correlations among buses. However, the limited quantity and quality of the sampling data restrict the implementation of data-driven recognition. In this paper, a physical-probabilistic-network (PPN) model applied for inferring overall operation mode of distribution networks is proposed. Based on which, a belief propagation-based algorithm is proposed for the inference even under situations when there are only partial bus voltages data available. Meanwhile, the required variable for inference can be reduced from the active trail analysis. Experiment results are used to compare its performance with classic methods and to prove its effectiveness and advantages.

Distributed Topology Identification Information Model of Distribution Network Based on IEC61850

This paper proposes a distributed topology information model based on IEC61850 to support the distributed topology processing function of the distribution network automation system. The information model expands the new logical nodes and common data classes for storing local topology information of local subgraphs and communication information of adjacent intelligent electronic devices. By using the distributed adaptation of graph connectivity algorithm and the extended IEC61850 information model, the dynamic topology identification function of the distribution network structure is realized. The extended information model and topology recognition algorithm are verified by the cyber-physical simulation system.

Control of Petri nets subject to strict temporal constraints using Max-Plus algebra

ABSTRACTIn this paper, we treat the control problem of timed discrete event systems under temporal constraints. This type of constraint is very frequent in production systems, transportation network and in networked automation systems. Precisely, we are interested in the validation of strict temporal constraints imposed on the paths in a timed event graph (TEG) by using Max-Plus algebra. Not all the transitions of the considered TEG model are controllable, i.e. only the input transitions are controllable. An analytical approach for computing state feedback controllers is developed. Sufficient condition is given for the existence of causal control laws satisfying the temporal constraints. In the first, a TEG with observable transitions is considered. Then, the proposed approach is extended to the partially observable TEG. The synthesised feedback can be interpreted by places of control connected to the TEG to guarantee the respect of the time constraints. The proposed method is illustrated in the assembly system example.

Study of Information Fusion of Distribution Network Automation and Digital Substation Automation

Information fusion of distribution network automation and digital substation automation can improve the efficient use of the digital substation’s distribution network data and strengthen the distribution network. The scheme adds a distribution network area controller for information interaction and integrally models distribution network and digital substation equipment based on the IEC 61850 protocol. This paper details the information fusion scheme of regional distribution network and substation automation system as well as the main function of the controller. The case study demonstrates that the fusion strategy can make the information collection more direct and the fault elimination more intelligent when dealing with the defects and faults of the distribution network.

Closed-loop control of constrained discrete event systems: application to a networked automation system

In this paper, we are interested in the design of closed-loop control laws to satisfy a set of temporal constraints in discrete event systems modeled by timed event graphs (TEGs). The dynamic behavior of the TEG is represented by a system of linear equations in Max-Plus algebra. Temporal constraints are imposed on some paths of the TEG and are expressed by a set of Max-Plus linear inequalities. The proposed approach is applied to the control of a networked automation producer/consumer system under a temporal constraint. The temporal constraint to be satisfied is imposed on the response time of the considered networked automation system (NAS). The calculated control laws are causal feedbacks and can be represented by monitor places connected to the NAS model.

A time synchronization technique for coap-based home automation systems

With the advent of internet-of-things (IoT)-based home automation systems, time synchronization techniques for low power sensor modules are in high demand. The constrained application protocol (CoAP) was recently standardized for sensor networks by IETF and is becoming widely adopted for home automation systems by ETSI, OMA, and oneM2M. The network time protocol (NTP) is not applicable to home automation systems due to its limited computing resources. This paper proposes a lightweight time synchronization algorithm for CoAP-based home automation system networks. The CoAP option field and a shim header are used to include time-stamps in the home automation system. The proposed scheme can thus be applied to both IP-based and non-IP-based home automation systems. In experiments with several household devices having non-IP communication interfaces, experimental results show that the proposed technique gives an average error of 1 ms and a network overhead reduction of 17% when compared to the ideal NTP service.

Model Approximation and Controller Synthesis for H∞ Robust Control of Multiple Time Delay Transfer Functions

It is well known that the modeling issues in Dynamical systems in chemical processes, networked control systems and automation systems are very complex and model may contain subsystems with different delays. Because of the mathematical complexity, the robust control of these types of multiple time delay system is a challenging one. The problem becomes more difficult and complex when the system is having time delays in both the denominator and the numerator. In this paper a new method is proposed for approximating general multiple time delay continuous-time transfer function system with multiple time delays in both the denominator and the numerator to a single input/output delay. Both Single Input Single Output(SISO) and Multi Input Multi Output(MIMO) cases have been considered. In this proposed methodology, the Approximated Generalized Time Moments (AGTM)/ Approximated Generalized Markov Parameter (AGMP) methods are used to transform the multiple time delay system into a single input/output delay system. A Linear Matrix Inequality (LMI) approach is developed for synthesizing robust H∞ control of the approximated time delay system. The efficacy of the proposed method is shown through illustrative examples. It is evident from the simulation results that the approximated system is stable with the proposed LMI H∞ controller.

Model checking response times in Networked Automation Systems using jitter bounds

Response time (RT) of Networked Automation Systems (NAS) is affected by timing imperfections induced due to the network, computing and hardware components. Guaranteeing RT in the presence of such timing imperfections is essential for building dependable NAS, and to avoid costly upgrades after deployment in industries.This investigation proposes a methodology and work-flow that combines modelling, simulation, verification, experiments, and software tools to verify the RT of the NAS during the design, rather than after deployment. The RT evaluation work-flow has three phases: model building, modelling and verification. During the model building phase component reaction times are specified and their timing performance is measured by combining experiments with simulation. During the modelling phase, component based mathematical models that capture the network architecture and inter-connection are proposed. Composition of the component models gives the NAS model required for studying the RT performance on system level. Finally, in the verification step, the NAS formal models are abstracted as UPPAAL timed automata with their timing interfaces. To model timing interfaces, the action patterns, and their timing wrapper are proposed. The formal model of high level of abstraction is used to verify the total response time of the NAS where the reactions to be verified are specified using a subset of timed computation tree logic (TCTL) in UPPAAL model checker. The proposed approach is illustrated on an industrial steam boiler deployment.

Design of Networked Home Automation System Based on μCOS-II and AMAZON

In recent years, with the popularity of computers and smart phones and the development of intel- ligent building in electronics industry, people's requirement of living environment is gradually changing. The intelligent home furnishing building has become the new focus of people purchasing. And the networked home automation system which relies on the advanced network technology to connect with air conditioning, lighting, security, curtains, TV, water heater and other home furnishing systems into a local area network becomes a net- worked control system. μC /OS is a real-time operating system with the free open-source code, the compact structure and the preemptive real-time kernel. In this paper, the author focuses on the design of home furnishing total controller based on AMAZON multimedia processor and μC/OS-II real-time operating system, and achieves the remote access connection and control through the Ethernet.