Performance analysis of Named Data Networking

Title :- Deep Reinforcement Learning-Based Adaptive Forwarding Strategy for Named Data Networking
Implementation Plan:
----------------------------
Step 1: Initially we construct a NDN-network with 5-Nodes.
Step 2: Then we integrate the RL agents into our network.
Step 3: Next we design and train DNN models.
Step 4: Then we Integrate RL agents and DNNs with NDNSimulator to enable communication and interaction within the NDN environment.
Step 5: Finally we get the performance metrics
5.1: Packet Delivery Ratio (PDR)
5.2: End-to-End Delay
5.3: Throughput
5.4: Resource Utilization
Software requirements:
--------------------------------
1) Development tool: Ns-3.35
2) Operating System: Ubuntu 20.04
Note:
---------
1) If the above plan does not satisfy your requirement, please provide the processing details, like the above step-by-step.
2) Please note that this implementation plan does not include any further steps after it is put into implementation.
/////////////////////////////////////////////////////////////////////////////////////////////////////////////
All types of network simulation tools support for your network research ideas such as
NS3, OMNET++, MATLAB, MININET, NS2, OPNET, PYTHON, COOJA, CONTIKI OS, QUALNET,
OPNET, NETSIM, GNS3, RTOOL, OPTISYSTEM, ONESIM …. will be supported under one roof.
We would be delighted to extend our support in utilizing network simulation tools to effectively resolve any network research challenges that you may encounter.
For further support
visit us at : networksimulat...
Mail us at : [e-mail]
call us at : 94448 47435