Contextual dimensions for cache replacement schemes in information-centric networks: a systematic review

Area of Science:

• Computer Science
• Network Engineering

Background:

• Information-Centric Networks (ICNs) offer efficient content distribution for applications like IoT, VANET, and MEC.
• In-network caching is crucial for ICN performance, with numerous cache replacement strategies proposed.
• Existing research often evaluates policies in varied contexts but lacks analysis of how context impacts performance.

Purpose of the Study:

• To systematically review the literature on Information-Centric Network cache replacement policies.
• To understand the influence of context characteristics on cache policy performance.
• To classify policies based on context dimensions and identify context-specific network enhancements.

Main Methods:

• Conducted a Systematic Literature Review (SLR) of ICN research.
• Analyzed studies focusing on cache replacement schemes and their performance.
• Mapped evidence of context aspects influencing cache behavior.

Main Results:

• Defined 'context' from the perspective of ICN cache replacement policies.
• Identified key context characteristics that significantly influence cache behavior.
• Classified cache replacement policies based on context dimensions for content relevance determination.

Conclusions:

• Contextual understanding is vital for effective Information-Centric Network (ICN) cache replacement policy design.
• The study provides a framework for selecting policies based on specific network contexts.
• Identified cache-enabled networks and their characteristics that improve cache eviction processes.