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A Runtime Adaptation Concept to reinforce Versatility in Industrial Automation / Titelei/Inhaltsverzeichnis
A Runtime Adaptation Concept to reinforce Versatility in Industrial Automation / Titelei/Inhaltsverzeichnis
Contents
Chapter
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I–XII
Titelei/Inhaltsverzeichnis
I–XII
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1–5
1 Introduction
1–5
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1.1 Motivation
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1.1.1 Applications and Scenarios
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1.1.2 Problem Definition
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1.2 Objective of this Work
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1.3 Structure of the Dissertation
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6–22
2 State of the Art
6–22
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2.1 Dynamic RunTime Environments (RTE)
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2.2 Virtual Machines
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2.3 Container Technology
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2.3.1 Docker-Daemon
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2.3.2 Load Distribution
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2.3.3 Compatibility
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2.4 Migration and States Synchronization
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2.4.1 Service Migration in Automation
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2.4.2 Redundancy Migration
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2.5 Components in Automation
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2.5.1 Single Control Unit (SCU)
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2.5.2 Group Control Unit (GCU)
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2.5.3 Procedures
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2.5.4 Inner Structure of a Process Control Component
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2.5.5 Adaptation in Industrial Automation Systems
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2.6 Methodological Fundamentals - Graph Theory
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2.6.1 Bipartite Graph
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2.6.2 Adjacency Matrix
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2.6.3 Star Topology
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2.6.4 Hub and Spoke Topology
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2.6.5 Mesh Topology
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2.6.6 Kn - Kn Topology
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2.6.7 Neighbor
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2.6.8 Valency
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2.7 Methodology - Load Distribution
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2.7.1 Load Distribution Algorithms
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2.7.2 Multi-Core Processing Analysis
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2.7.3 Consensus Networks
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2.7.4 Semi-Definite Programming
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2.7.5 MATLAB-YALMIP
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2.7.6 Simulated Annealing
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2.7.7 Optimal Distribution Solvers - Z3 SMT Solver
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2.7.8 Deployment in Automotive Open System Architecture (AUTOSAR)
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2.8 Agents Systems
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2.9 Market-based Multi-Agent-System Approach
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2.10 Agents Systems Hierarchy in Automation
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2.11 Agent-Based Planning of Production Sequences
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2.12 Recipes Definitions
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2.13 Tools - Discovery
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2.13.1 Bonjour Protocol
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2.13.2 Mechanism of Operation
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2.13.3 Reconfiguration of Real-Time Fieldbus
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23–36
3 Runtime Adaptation Concept
23–36
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3.1 Terminology and Definitions
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3.2 Concept Overview
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3.3 Process
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3.3.1 Component redeployment
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3.3.2 Container Redeployment
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3.4 Controller
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3.4.1 Optimization Criteria and Constraints
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3.4.2 Boundary Conditions
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3.4.3 Stability, Performance Analysis and Performance Enhancement
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3.5 Actuator
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3.5.1 Load Distribution Executor
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3.6 Sensor
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3.6.1 Resources & Component Manifestation
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3.7 Disturbance
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3.8 Architecture Overview
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37–39
4 Modeling Fundamentals
37–39
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4.1 The Load Balancing Model
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4.1.1 Network Model
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4.1.2 Load Model
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4.1.3 Mathematical Model
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40–54
5 Methodology Investigation - Analytical Approach - Linear Model
40–54
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5.1 Modeling of the Adaption Algorithms
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5.2 Model Characteristics
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5.3 Model
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5.3.1 Stability and Convergence Analysis
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5.3.2 System Dynamic and Performance Analysis
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5.4 Modeling of Multidimensional Loads
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5.4.1 MD Problem Classification
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5.4.2 MD Problem Modeling
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5.5 Performance Enhancement via Regression Models
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5.5.1 Optimizing the Transfer Coefficient
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5.5.2 Ring Hub and Spoke Networks
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5.5.3 Regression Model
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55–64
6 Methodology Investigation - Empirical Approach - Non-Linear Model
55–64
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6.1 Model Characteristics
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6.2 Performance Assessment
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6.3 KPIs Preliminaries
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6.3.1 Network Topology
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6.3.2 Load Description
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6.3.3 Initial Conditions
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6.3.4 Node Capacity
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6.3.5 Probabilistic Algorithms
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6.3.6 Foreknowledge of Terminating Conditions
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6.4 KPIs
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6.4.1 Qualitative KPIs
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6.4.2 Quantitative KPIs
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6.4.3 Modular Benchmark
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6.4.4 Benchmark Testing
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65–72
7 Use-Case - Implementation Approach
65–72
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7.1 Demonstrator - SMS-SEMAG Cold Rolling Mill
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7.1.1 Devices
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7.1.2 Single and Group Function Units (SFU and GFU)
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7.2 Load Balancing
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73–84
8 Implementation - Reality Approach
73–84
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8.1 Decentral Algorithm (Resources Perspective)
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8.1.1 Preliminaries
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8.1.2 Objective
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8.1.3 The BRAD Algorithm - Mechanism of Operation
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8.1.4 Simulation Assessment
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8.2 Agents Systems Approach (Components Perspective)
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85–96
9 Scenario 1 - Decentralized Algorithm
85–96
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9.1 Realization
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9.1.1 Sync. State Machine BRAD
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9.1.2 Application Monitor
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9.1.3 Node to Node (N2N) Discovery
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9.1.4 Device Resources Monitoring
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9.1.5 Neighbor Informer
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9.1.6 Neighbor Data Bank
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9.1.7 TSE Optimizer - Sender End
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9.1.8 Request Sender
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9.1.9 Request Receiver
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9.1.10 TSE Optimizer - Receiver End
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9.1.11 Acceptance Notifier
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9.1.12 Send Initiator
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9.1.13 Redeployer
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9.2 Performance Assessment
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9.2.1 Setup
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9.2.2 Scenario
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97–104
10 Scenario 2 - Agents System
97–104
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10.1 Realization
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10.1.1 Agent Load Balancing Algorithm
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10.2 Performance Assessment
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10.2.1 Setup
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10.2.2 Scenario
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105–109
11 Conclusion and Outlook
105–109
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11.1 Outlook
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11.1.1 Algorithm Enhancement
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11.1.2 Synchronization
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11.1.3 Improvements for Load Model
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11.1.4 Improvements in the Decentralized Algorithm
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11.2 Improvements in the Infrastructure
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11.3 Further Utilizations of Agents Systems Approach
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110–118
Bibliography
110–118
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A Runtime Adaptation Concept to reinforce Versatility in Industrial Automation , page I - XII
Titelei/Inhaltsverzeichnis
Autoren
Haitham Elfahaam
DOI
doi.org/10.51202/9783186267085-I
ISBN print: 978-3-18-526708-6
ISBN online: 978-3-18-626708-5
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