scholarly journals Queuing over Ever-changing Communication Scenarios in Tactical Networks

2020 ◽  
Author(s):  
Roberto Rigolin F. Lopes ◽  
Pooja Hanavadi Balaraju ◽  
Paulo H. Rettore ◽  
Peter Sevenich
Keyword(s):  
Control Systems ◽  
Information Exchange ◽  
Data Rate ◽  
Cross Layer ◽  
Buffer Occupancy ◽  
Data Flows ◽  
Tactical Networks ◽  
Quantitative Results ◽  
Using Data ◽  
And Control

This paper introduces a hierarchy of queues complementing each other to handle ever-changing communication scenarios in tactical networks. The first queue stores the QoS-constrained messages from command and control systems. These messages are fragmented into IP packets, which are stored in a queue of packets (second) to be sent to the radio buffer (third), which is a queue with limited space therefore, open to overflow. We start with the hypothesis that these three queues can handle ever-changing user(s) data flows (problem A) through ever-changing network conditions (problem B) using cross-layer information exchange, such as buffer occupancy, data rate, queue size and latency (problem A|B). We introduce two stochastic models to create sequences of QoS-constrained messages (A) and to create ever-changing network conditions (B). In sequence, we sketch a control loop to shape A to B to test our hypothesis using model A|B, which defines enforcement points at the incoming/outgoing chains of the system together with a control plane. Then, we discuss experimental results in a network with VHF radios using data flows that overflows the radio buffer over ever-changing data rate patterns. We discuss quantitative results showing the performance and limitations of our solutions for problems A, B and A|B.

scholarly journals Queuing over Ever-changing Communication Scenarios in Tactical Networks

2020 ◽  
Author(s):  
Roberto Rigolin F. Lopes ◽  
Pooja Hanavadi Balaraju ◽  
Paulo H. Rettore ◽  
Peter Sevenich
Keyword(s):  
Control Systems ◽  
Information Exchange ◽  
Data Rate ◽  
Cross Layer ◽  
Buffer Occupancy ◽  
Data Flows ◽  
Tactical Networks ◽  
Quantitative Results ◽  
Using Data ◽  
And Control

This paper introduces a hierarchy of queues complementing each other to handle ever-changing communication scenarios in tactical networks. The first queue stores the QoS-constrained messages from command and control systems. These messages are fragmented into IP packets, which are stored in a queue of packets (second) to be sent to the radio buffer (third), which is a queue with limited space therefore, open to overflow. We start with the hypothesis that these three queues can handle ever-changing user(s) data flows (problem A) through ever-changing network conditions (problem B) using cross-layer information exchange, such as buffer occupancy, data rate, queue size and latency (problem A|B). We introduce two stochastic models to create sequences of QoS-constrained messages (A) and to create ever-changing network conditions (B). In sequence, we sketch a control loop to shape A to B to test our hypothesis using model A|B, which defines enforcement points at the incoming/outgoing chains of the system together with a control plane. Then, we discuss experimental results in a network with VHF radios using data flows that overflows the radio buffer over ever-changing data rate patterns. We discuss quantitative results showing the performance and limitations of our solutions for problems A, B and A|B.

scholarly journals Quantizing Radio Link Data Rates to Create Ever-changing Network Conditions in Tactical Networks

2020 ◽  
Author(s):  
Roberto Rigolin F. Lopes ◽  
Johannes Loevenich ◽  
Paulo H. Rettore ◽  
Sharath M. Eswarappa ◽  
Peter Sevenich
Keyword(s):  
Field Experiments ◽  
Time Window ◽  
Data Rate ◽  
Radio Link ◽  
Data Rates ◽  
Data Flows ◽  
Packet Latency ◽  
Tactical Networks ◽  
Link Data ◽  
And Control

Several sources of randomness can change the radio link data rate at the edge of tactical networks. Simulations and field experiments define these sources of randomness indirectly by choosing the mobility pattern, communication technology, number of nodes, terrain, obstacles and so on. Therefore, the distribution of change in the network conditions is unknown until the experiment is executed. We start with the hypothesis that a model can quantize the network conditions, using a set of states updated within a time window, to define and control the distribution of change in the link data rate before the experiment is executed. The goal is to quantify how much variation in the link data rate a tactical system can handle and how long it takes to resume IP data-flows after link disconnections. Our model includes functions to combine patterns of change together, transforming one pattern into another, jumping between patterns, and creating loops among different patterns of change. We use exemplary patterns to show how the change in the data rate impacts other link metrics, such as latency and jitter. Our hypothesis is verified with experiments using VHF radios over different patterns of change created by our model. We compute the inter-packet latency of three types of IP data-flows (broadcast, unicast and overlay) to highlight the time to resume data-flows after long link disconnections. The experimental results also support the discussion on the advantages and limitations of our model, which was designed to test tactical systems using military radios.

scholarly journals Quantizing Radio Link Data Rates to Create Ever-changing Network Conditions in Tactical Networks

2020 ◽  
Author(s):  
Roberto Rigolin F. Lopes ◽  
Johannes Loevenich ◽  
Paulo H. Rettore ◽  
Sharath M. Eswarappa ◽  
Peter Sevenich
Keyword(s):  
Field Experiments ◽  
Time Window ◽  
Data Rate ◽  
Radio Link ◽  
Data Rates ◽  
Data Flows ◽  
Packet Latency ◽  
Tactical Networks ◽  
Link Data ◽  
And Control

Several sources of randomness can change the radio link data rate at the edge of tactical networks. Simulations and field experiments define these sources of randomness indirectly by choosing the mobility pattern, communication technology, number of nodes, terrain, obstacles and so on. Therefore, the distribution of change in the network conditions is unknown until the experiment is executed. We start with the hypothesis that a model can quantize the network conditions, using a set of states updated within a time window, to define and control the distribution of change in the link data rate before the experiment is executed. The goal is to quantify how much variation in the link data rate a tactical system can handle and how long it takes to resume IP data-flows after link disconnections. Our model includes functions to combine patterns of change together, transforming one pattern into another, jumping between patterns, and creating loops among different patterns of change. We use exemplary patterns to show how the change in the data rate impacts other link metrics, such as latency and jitter. Our hypothesis is verified with experiments using VHF radios over different patterns of change created by our model. We compute the inter-packet latency of three types of IP data-flows (broadcast, unicast and overlay) to highlight the time to resume data-flows after long link disconnections. The experimental results also support the discussion on the advantages and limitations of our model, which was designed to test tactical systems using military radios.

ADDER

2021 ◽  
pp. 49-56
Author(s):  
A. N. Brysin ◽  
Yu. A. Zhuravleva ◽  
A. S. Mikaeva ◽  
S. A. Mikaeva
Keyword(s):  
Control Systems ◽  
Information Exchange ◽  
Electricity Generation ◽  
Local Network ◽  
Exchange Of Information ◽  
Upper Level ◽  
Bidirectional Exchange ◽  
And Control ◽  
Ethernet Interface

The article describes an electronic multifunctional adder for electricity metering SEM-3. The authors give the technical characteristics, the device and the principle of its operation. The presented adder is designed to monitor and account for the consumption of electricity generation and power directly from consumers, as well as in automated centralized accounting and control systems, and is designed for round-the-clock operation. The adder can collect and transmit information over six independent serial interfaces. The adder with a builtin GSM module provides bidirectional information exchange via cellular modem communication with remote devices and the transfer of accumulated data to the upper level of the automated electricity metering system. It provides bidirectional exchange of information over a local network with a PC over the built-in 10/100 Base-T Ethernet interface.

Information protection to prevent failures of elements of automated information and control systems of power facilities

2021 ◽  
Vol 94 ◽  
pp. 144-155
Author(s):  
E. P. Grabchak ◽  
◽  
E. L. Loginov ◽  
Keyword(s):  
Information Security ◽  
Control Systems ◽  
Power Supply ◽  
Information Exchange ◽  
Control Process ◽  
Reference Sequence ◽  
Security Threats ◽  
Power Equipment ◽  
Intelligent Methods ◽  
And Control

Introduction. One of the most important tasks in achieving reliability and safety of power supply as an element of ensuring technospheric security is the modernization of automated information and control systems for the transmitting and receiving sides, which ensures resistance against known types of attacks. The aim of the study is to solve the problem of secure information exchange within the framework of automated information and control systems, taking into account the low security of technological communication channels of power facilities to achieve the reliability and safety of power supply as an element of ensuring technospheric security based on the development of intelligent methods for detecting dangerous influences and intrusions to neutralize information security threats in relation to commands to control power equipment. Research methods. Within the framework of the study, general scientific and special methods of scientific knowledge were used, including analysis, synthesis, generalization, which were based on the main provisions and patterns of behavior of systems and information theory. Research results. It is proposed to create innovative algorithms for controlling power equipment, built on the basis of libraries of reference commands and reference sequences of commands used to replace commands intentionally or accidentally distorted by erroneous bits, as well as diagnosing vulnerabilities of information and control systems to ensure the correctness of the process of controlling power equipment. Conclusion. The listed technologies will make it possible to create a new class of efficient algorithms for power equipment control, built on the basis of intelligent methods for detecting dangerous influences and intrusions to neutralize information security threats in relation to control commands based on the analysis of high-level behavioral characteristics of the protected information and control system with the function of controlling the transition of the controlled system to the next a condition that depends on the exact correspondence of the generated commands to the reference commands and the reference sequence of commands, which will ensure the correctness of the control process of power equipment. Key words: energy, information and control networks, reliability, security, power supply, algorithms, monitoring, protection, information.

scholarly journals Fault detection Automation in Distributed Control Systems using Data-driven methods: SVM and KNN

2021 ◽  
Author(s):  
Seyed Hossein Ahmadi
Keyword(s):  
Control Systems ◽  
Distributed Control ◽  
Power Distribution ◽  
Gas Turbines ◽  
Distribution Systems ◽  
Diagnostic Methods ◽  
Power Distribution Systems ◽  
Distributed Control Systems ◽  
Using Data ◽  
And Control

<p>Fault diagnostic methods with fuzzy logic methods, SVM, KNN and artificial intelligence systems have been used in complex systems such as wind turbines, gas turbines, power distribution systems, power transformers and rotary machines, but in the specific field of distributed control systems, the vacancy of this topic is strongly felt. Due to the need of the industry to detect faults quickly and in a timely manner in all modes of sensors, actuators, outputs and control logics to maintain expensive, valuable resources, important and complex equipment, it is very necessary to enter this topic. In this paper, a suitable theoretical and practical basis for diagnosing various types of faults in the DCS of a gas refinery is done. The fact that the operator quickly identifies the area and the cause of the fault can avoid huge losses in terms of downtime. Automation of fault diagnosis in DCS has not been explicitly mentioned in any article or book, and here the plan is presented for the first time. In this design, we connect MATLAB classification apps to the industrial system like DCS, then data are analyzed by SVM and KNN methods to detect faults. The results show that faults can be detected with a probability of more than 85% accuracy without the need for on-site expert force and with much less time.</p>

scholarly journals Fault detection Automation in Distributed Control Systems using Data-driven methods: SVM and KNN

2021 ◽  
Author(s):  
Seyed Hossein Ahmadi ◽  
Mohammad Javad Khosrowjerdi
Keyword(s):  
Control Systems ◽  
Distributed Control ◽  
Power Distribution ◽  
Gas Turbines ◽  
Distribution Systems ◽  
Diagnostic Methods ◽  
Power Distribution Systems ◽  
Distributed Control Systems ◽  
Using Data ◽  
And Control

<p>Fault diagnostic methods with fuzzy logic methods, SVM, KNN and artificial intelligence systems have been used in complex systems such as wind turbines, gas turbines, power distribution systems, power transformers and rotary machines, but in the specific field of distributed control systems, the vacancy of this topic is strongly felt. Due to the need of the industry to detect faults quickly and in a timely manner in all modes of sensors, actuators, outputs and control logics to maintain expensive, valuable resources, important and complex equipment, it is very necessary to enter this topic. In this paper, a suitable theoretical and practical basis for diagnosing various types of faults in the DCS of a gas refinery is done. The fact that the operator quickly identifies the area and the cause of the fault can avoid huge losses in terms of downtime. Automation of fault diagnosis in DCS has not been explicitly mentioned in any article or book, and here the plan is presented for the first time. In this design, we connect MATLAB classification apps to the industrial system like DCS, then data are analyzed by SVM and KNN methods to detect faults. The results show that faults can be detected with a probability of more than 85% accuracy without the need for on-site expert force and with much less time.</p>

scholarly journals Fault detection Automation in Distributed Control Systems using Data-driven methods: SVM and KNN

2021 ◽  
Author(s):  
Seyed Hossein Ahmadi
Keyword(s):  
Control Systems ◽  
Distributed Control ◽  
Power Distribution ◽  
Gas Turbines ◽  
Distribution Systems ◽  
Diagnostic Methods ◽  
Power Distribution Systems ◽  
Distributed Control Systems ◽  
Using Data ◽  
And Control

<p>Fault diagnostic methods with fuzzy logic methods, SVM, KNN and artificial intelligence systems have been used in complex systems such as wind turbines, gas turbines, power distribution systems, power transformers and rotary machines, but in the specific field of distributed control systems, the vacancy of this topic is strongly felt. Due to the need of the industry to detect faults quickly and in a timely manner in all modes of sensors, actuators, outputs and control logics to maintain expensive, valuable resources, important and complex equipment, it is very necessary to enter this topic. In this paper, a suitable theoretical and practical basis for diagnosing various types of faults in the DCS of a gas refinery is done. The fact that the operator quickly identifies the area and the cause of the fault can avoid huge losses in terms of downtime. Automation of fault diagnosis in DCS has not been explicitly mentioned in any article or book, and here the plan is presented for the first time. In this design, we connect MATLAB classification apps to the industrial system like DCS, then data are analyzed by SVM and KNN methods to detect faults. The results show that faults can be detected with a probability of more than 85% accuracy without the need for on-site expert force and with much less time.</p>

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