An Efficient Distributed Content Store-Based Caching Policy for Information-Centric Networking.

Area of Science:

• Computer Science
• Networking

Background:

• Information-centric networking (ICN) relies on content stores (CS) for caching and retrieval.
• Current ICN designs often fail to leverage CS information for coordinated caching and retrieval.
• Independent operation of node CS and reliance on FIB for Interest packet forwarding limit network efficiency.

Purpose of the Study:

• To highlight the importance of CS information for efficient content caching and retrieval in ICN.
• To improve ICN performance, particularly in resource-constrained environments like the Internet of Things (IoT).
• To propose a distributed caching policy coordinating CS among neighboring nodes.

Main Methods:

• Proposed an efficient caching policy to coordinate CS of a node with its neighbors in a distributed manner.
• Enabled CS information in the data plane for efficient transmission and coordination.
• Each node maximizes unique popular content objects in its CS not present in neighbors' CS.
• Implemented the policy on state-of-the-art popularity-based caching schemes.

Main Results:

• Significant improvement in cache hit ratio.
• Reduced stretch ratio.
• Lowered content retrieval latency.
• Enhanced energy efficiency compared to existing schemes.

Conclusions:

• Coordinated CS information significantly enhances ICN performance.
• The proposed distributed policy effectively improves caching and retrieval efficiency.
• This approach is particularly beneficial for resource-constrained IoT environments.