SDN NDN Projects examples using omnet++

The Software-Defined Networking (SDN) and Named Data Networking (NDN) are two powerful networking models that can be integrated to improve the network efficiency, flexibility, and security and then the SDN allows centralized control of the network across a programmable controller since the NDN concentrates on data-centric communication in which the data is addressed by names rather than IP addresses. Using OMNeT++ to emulate the SDN and NDN can lead to valuable research on how these models can be incorporated and enhanced. The given below are the some of the sample projects that discover the intersection of SDN and NDN using OMNeT++:

Integration of SDN and NDN for Efficient Content Delivery

Description: To mimic the integration of SDN and NDN to enhance the content delivery in a network, that concentrates on enhancing the data retrieval times and minimizing the network congestion.

Key Features:

Execution of an SDN controller that handles the NDN routing tables and content forwarding strategies.
Mimic the scenarios with changing content request patterns, network topologies, and traffic loads.
To analysis the metric such as data retrieval latency, bandwidth utilization, and cache hit ratio.

Tools & Frameworks:

NDNSim (NDN Simulator) + INET + Custom SDN Controller: Use NDNSim for NDN simulation, incorporates it with INET for networking capabilities, and build a custom SDN controller module to handle the NDN operations.

Dynamic Routing in SDN-Enabled NDN Networks

Description: Discovering the dynamic routing methods in SDN-enabled NDN networks, in which the SDN controller enhance the NDN content routing based on real-time network conditions.

Key Features:

Execution of dynamic routing techniques that permits the SDN controller to adapts the NDN forwarding paths in response to network congestion, link failures, or changes in demand.
Mimic the network scenarios with changing levels of traffic, node mobility, and link reliability.
To analysis the metrics such as path stability, data delivery success rate, and network adaptability.

Tools & Frameworks:

NDNSim + Custom SDN Modules: Expand NDNSim to contain the SDN-based dynamic routing capabilities and emulate numerous network scenarios.

Security in SDN-Enabled NDN Networks

Description: Examining security mechanisms in SDN-enabled NDN networks that concentrate on protecting data integrity, mitigating the cache poisoning attacks, and ensuring secure communication.

Key Features:

Execution of security protocols that influence SDN’s centralized control and NDN’s data-centric approach to secure against numerous network attacks.
Mimic of attack scenarios like cache poisoning, data tampering, and unauthorized content access.
To assess the security effectiveness, effects on network performance, and the trade-offs among the security and efficiency.

Tools & Frameworks:

NDNSim + INET + Custom Security Modules: Build and emulate the security protocols for SDN-enabled NDN networks, that incoporates them with NDNSim and INET.

QoS Management in SDN-Enabled NDN Networks

Description: Emulate the Quality of Service (QoS) management in SDN-enabled NDN networks to make sure that various kinds of content meet their particular QoS requirements.

Key Features:

Execution of QoS-aware routing and forwarding strategies that permits the SDN controller to select the NDN traffic based on content type, delay sensitivity, and bandwidth requirements.
Ape the scenarios with mixed traffic types that has video streaming, file downloads, and real-time communication.
To analysis in terms of QoS satisfaction, resource allocation efficiency, and overall network throughput.

Tools & Frameworks:

NDNSim + Custom QoS Modules: Expand the NDNSim to support QoS management in an SDN-enabled NDN environment and measure its performance.

Caching Strategies in SDN-Enabled NDN Networks

Description: Discovering advanced caching approaches in SDN-enabled NDN networks, in which the SDN controller handles the content caching decisions to enhance the data availability and minimize the latency.

Key Features:

Execution of caching techniques that permits the SDN controller to enthusiastically handles the placement and replacement of cached content via the network.
Mimic the scenarios with changing content popularity, cache sizes, and network topologies.
To analysis the metrics such as cache hit ratio, data retrieval latency, and network bandwidth savings.

Tools & Frameworks:

NDNSim + Custom Caching Modules: Build the caching approaches for SDN-enabled NDN networks and incorporates them with NDNSim for simulation.

Mobility Management in SDN-Enabled NDN Networks

Description: Examining mobility management approaches in SDN-enabled NDN networks, in which the mobile nodes often change their network locations.

Key Features:

Execution of mobility management protocols that permits the SDN controller to seamlessly manages the varying in network topology due to node mobility, make sure continuous access to NDN content.
Mimic the scenarios with changing levels of node mobility, handoff frequency, and network density.
To analysis the performance metrics such as handover latency, packet loss, and the impact of mobility on content delivery.

Tools & Frameworks:

NDNSim + Custom Mobility Modules: To build the mobility management approaches and emulate the efficiency in an SDN-enabled NDN environment.

Load Balancing in SDN-Enabled NDN Networks

Description: Mimicking the load balancing approaches in SDN-enabled NDN networks to allocate network traffic evenly and prevent congestion.

Key Features:

Execution of load balancing techniques that enable the SDN controller to enthusiastically adapts the NDN forwarding paths based on network load and resource availability.
Mimic the scenarios with changing the traffic patterns, network topologies, and content demand.
To analysis the performance metrics such as network throughput, latency, and load distribution efficiency.

Tools & Frameworks:

NDNSim + Custom Load Balancing Modules: Build and emulate the load balancing approaches for SDN-enabled NDN networks.

Scalability Analysis of SDN-Enabled NDN Networks

Description: Discovering the scalability of SDN-enabled NDN networks by emulated the large-scale networks with thousands of nodes and high traffic volumes.

Key Features:

To mimic the large-scale networks with changing the numbers of nodes, data sources, and content consumers.
Analysis of performance in terms of control plane scalability, data plane efficiency, and the effects of network size on overall performance.
Examination of strategies to improve the scalability like hierarchical SDN controllers and distributed caching.

Tools & Frameworks:

NDNSim + INET + Custom Scalability Modules: To mimic the large-scale SDN-enabled NDN networks and measure their performance in numerous scalability conditions.

Cross-Layer Optimization in SDN-Enabled NDN Networks

Description: Examining the cross-layer optimization approach in SDN-enabled NDN networks in which the SDN controller enhances multiple layers of the network stack to optimize the performance.

Key Features:

Execution of cross-layer methods that incorporates the physical layer modulation, MAC protocols, and NDN content forwarding in an SDN context.
Mimic the scenarios with changing network conditions, device capabilities, and traffic demands.
To analysis the metrics such as system throughput, latency, energy efficiency, and communication reliability.

Tools & Frameworks:

NDNSim + Custom Cross-Layer Modules: Improve and mimic the cross-layer optimization methods for SDN-enabled NDN networks.

Resource Management in SDN-Enabled NDN Networks

Description: Discovering the resource management approaches in SDN-enabled NDN networks to enhance the use of network resources like bandwidth, cache storage, and processing power.

Key Features:

Execution of resource management techniques that permits the SDN controller to distribute the network resources enthusiastically based on traffic demands and network conditions.
To mimic the scenarios with changing resource constraints, content demand, and network topologies.
To analysis the performance metrics such as resource utilization, QoS satisfaction, and network efficiency.

Tools & Frameworks:

NDNSim + Custom Resource Management Modules: Build and emulate the resource management approaches for SDN-enabled NDN networks.

In the conclusion, we clearly discussed about the Software-Defined Networking- Named Data Networking projects objectives and the simulation explanations that were enforce in OMNeT++ tool. Also we elaborate further information regarding Software-Defined Networking- Named Data Networking.

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