Content Centric Networking (CCN):
- An emerging paradigm that grounds networking primitives on content names rather than node locators.
- CCN affords efficient caching capabilities and ensures high content availability
- Network traffic reduction, and low retrieval latency which reduces congestion and improve end-to-end delay.
◘ [Python] - Python is an interpreted, high-level, general-purpose programming language ◘ [CCN] - Centric networking emphasizes content by making it directly addressable and routable ◘ [Reinforcement learning] - Reinforcement learning is an area of machine learning concerned with how software agents ought to take actions in an environment in order to maximize the notion of cumulative reward. ◘ [Q-learning] - Q-learning is a model-free reinforcement learning algorithm to learn a policy telling an agent what action to take under what circumstances
- implement the model
- couple this part of the code with the Ad-hoc script
- choose a cache replacement policy
- choose learning strategy "Scheduled, individual or hybrid"
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