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en:iot-reloaded:iot_network_design_tools [2024/12/09 18:59] – [4. IoT Network Topology Design Tools] pczekalskien:iot-reloaded:iot_network_design_tools [2025/05/13 10:43] (current) – pczekalski
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 ====== IoT Network Design Tools ====== ====== IoT Network Design Tools ======
-The design of a robust IoT (Internet of Things) network is fundamental to the success of any IoT project. A well-architected network ensures reliable communication between IoT devices, minimises latency, optimises power consumption, and enables efficient data transfer. However, building an IoT network is complex, requiring the integration of various technologies, protocols, and platforms. IoT network design tools assist in modelling, simulating, and managing the networks interconnecting the myriad IoT devices.+The design of a robust IoT network is fundamental to the success of any IoT project. A well-architected network ensures reliable communication between IoT devices, minimises latency, optimises power consumption, and enables efficient data transfer. However, building an IoT network is complex, requiring the integration of various technologies, protocols, and platforms. IoT network design tools assist in modelling, simulating, and managing the networks interconnecting the myriad IoT devices.
 This section explores the types of IoT network design tools, their features, and their use cases. A short list of tools is presented in the diagram {{ref>iontdtool1}}. This section explores the types of IoT network design tools, their features, and their use cases. A short list of tools is presented in the diagram {{ref>iontdtool1}}.
  
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 ==== Network Simulation Tools ==== ==== Network Simulation Tools ====
  
-Network simulation tools allow developers to virtually create and test IoT networks before deployment. These tools simulate the behaviour of devices, communication protocols, and network conditions, allowing for better planning, optimisation, and troubleshooting.+Before deployment, network simulation tools allow developers to create and test IoT networks virtually. These tools simulate the behaviour of devices, communication protocols, and network conditions, allowing for better planning, optimisation, and troubleshooting.
  
 **Common Tools**\\ **Common Tools**\\
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   * UVexplorer uses SNMP, ICMP, WMI, and other protocols to discover network devices.   * UVexplorer uses SNMP, ICMP, WMI, and other protocols to discover network devices.
-  * In an IoT network, it can identify connected devices such as sensors, gateways, and IoT hubs.+  * An IoT network can identify connected devices such as sensors, gateways, and IoT hubs.
  
 **2.Topology Mapping:** **2.Topology Mapping:**
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 **Possible use in IoT Network Design** **Possible use in IoT Network Design**
  
-  * Pre-Deployment: Helps in planning IoT devices' physical and logical layout by visualising the network.+  * Pre-Deployment: Helps planning IoT devices' physical and logical layout by visualising the network.
   * Post-Deployment: Validates the network design by ensuring all devices are correctly configured and connected.   * Post-Deployment: Validates the network design by ensuring all devices are correctly configured and connected.
   * Scalability: Assists in scaling IoT networks by providing insights into device distribution and potential expansion areas.   * Scalability: Assists in scaling IoT networks by providing insights into device distribution and potential expansion areas.
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   * It also helps identify underperforming devices or overloaded network segments.   * It also helps identify underperforming devices or overloaded network segments.
  
-  *3.  Custom Dashboards:+  *3. Custom Dashboards:
  
   * Allows the creation of dashboards tailored to specific IoT use cases, displaying critical metrics for the entire network.   * Allows the creation of dashboards tailored to specific IoT use cases, displaying critical metrics for the entire network.
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   * **Features:** Open-source performance testing tool that supports IoT network stress testing.   * **Features:** Open-source performance testing tool that supports IoT network stress testing.
-  * **Use Case:** Used to test the scalability and load-handling capabilities of IoT networks, including simulated device traffic.+  * **Use Case:** Used to test IoT networks' scalability and load-handling capabilities, including simulated device traffic.
   * **Key Benefits:** Detailed reporting, scalability, and extensibility.   * **Key Benefits:** Detailed reporting, scalability, and extensibility.
  
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 Designing efficient, reliable, and scalable IoT networks requires addressing challenges such as resource optimisation, communication reliability, scalability, energy efficiency, and security. Mathematical modelling is a powerful tool for tackling these challenges by providing a structured framework for analysing, simulating, and optimising IoT systems. Designing efficient, reliable, and scalable IoT networks requires addressing challenges such as resource optimisation, communication reliability, scalability, energy efficiency, and security. Mathematical modelling is a powerful tool for tackling these challenges by providing a structured framework for analysing, simulating, and optimising IoT systems.
  
-=== Key Applications of Mathematical Modeling in IoT Network Design ===+**Key Applications of Mathematical Modeling in IoT Network Design **
  
 **1. Network Topology Design**\\ **1. Network Topology Design**\\
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 **2. Resource Allocation and Optimisation**\\ **2. Resource Allocation and Optimisation**\\
-IoT networks have limited resources like bandwidth, energy, and computational power. Optimisation techniques, such as linear programming (LP), integer programming, and heuristic methods, are used to allocate resources effectively.+IoT networks have limited resources like bandwidth, energy, and computational power. To allocate resources effectively, Optimisation techniques, such as linear programming (LP), integer programming, and heuristic methods, are used.
  
   * **Example:** Energy-aware scheduling models optimise the energy consumption of sensor nodes to extend network lifetime.   * **Example:** Energy-aware scheduling models optimise the energy consumption of sensor nodes to extend network lifetime.
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 ==== System Dynamics Modelling as a Tool for Designing Secure and Efficient IoT Systems, Applications, and Networks ==== ==== System Dynamics Modelling as a Tool for Designing Secure and Efficient IoT Systems, Applications, and Networks ====
  
-The Internet of Things (IoT) is a transformative technological paradigm still in its early stages of development. As IoT adoption continues to grow, there is an opportunity to design systems that are scalable, energy-efficient, cost-effective, interoperable, and secure by design while maintaining an acceptable level of Quality of Service (QoS). Achieving these objectives requires a holistic, system-centric approach that balances stakeholders' diverse and sometimes conflicting goals, including network operators, service providers, regulators, and end users.+The Internet of Things is a transformative technological paradigm still in its early stages of development. As IoT adoption continues to grow, there is an opportunity to design systems that are scalable, energy-efficient, cost-effective, interoperable, and secure by design while maintaining an acceptable level of Quality of Service (QoS). Achieving these objectives requires a holistic, system-centric approach that balances stakeholders' diverse and sometimes conflicting goals, including network operators, service providers, regulators, and end users.
  
  
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 **3. Optimisation of Resource Utilisation:**\\ **3. Optimisation of Resource Utilisation:**\\
-SD can identify energy consumption, bandwidth allocation, and computational resource usage inefficiencies by modelling IoT networks, guiding cost and energy efficiency improvements.+SD can identify energy consumption, bandwidth allocation, and computational resource usage inefficiencies by modelling IoT networks and guiding cost and energy efficiency improvements.
  
 **4. Designing Secure IoT Systems:**\\ **4. Designing Secure IoT Systems:**\\
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 **1. Smart Agriculture (e.g., Rice Farming):**\\ **1. Smart Agriculture (e.g., Rice Farming):**\\
 As demonstrated in a study cited in ((M. G. S. Wicaksono, E. Suryani, and R. A. Hendrawan. Increasing productivity of rice plants As demonstrated in a study cited in ((M. G. S. Wicaksono, E. Suryani, and R. A. Hendrawan. Increasing productivity of rice plants
-based on iot (internet of things) to realise smart agriculture using system thinking approach.+based on iot (internet of things) to realise smart agriculture using a system thinking approach.
 Procedia Computer Science, 197:607–616, 2021.)), SD was used to develop causal loop diagrams to understand the interactions between environmental factors, IoT-enabled sensors, and farming outcomes. By identifying key leverage points, the researchers proposed IoT-based solutions to enhance rice productivity while minimising resource use. Procedia Computer Science, 197:607–616, 2021.)), SD was used to develop causal loop diagrams to understand the interactions between environmental factors, IoT-enabled sensors, and farming outcomes. By identifying key leverage points, the researchers proposed IoT-based solutions to enhance rice productivity while minimising resource use.
  
en/iot-reloaded/iot_network_design_tools.1733770797.txt.gz · Last modified: 2024/12/09 18:59 by pczekalski
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