Citation :

A R Charulatha, C. Victoria Priscilla, "A Novel Cuckoo Search-Based Caching Strategy in Content-Centric Networking," International Journal of Electronics and Communication Engineering, vol. 13, no. 5, pp. 30-40, 2026. Crossref, https://doi.org/10.14445/23488549/IJECE-V13I5P104

Abstract

The fast growth of content-related applications has underlined the need to have effective data retrieval schemes in Content-Centric Networking (CCN). CCN does not prioritize the host-based communication and instead retrieves information through names, placing caching at the centre of network performance. Commonly used traditional cache management schemes like LRU, LFU, and FIFO are easy to code and fail to scale to the changing user behaviour and changing content popularity. This paper seeks to overcome this weakness by coming up with a caching architecture using the Cuckoo Search (CS) optimization method. The algorithm formulates the caching problem as a multi-objective problem- to increase the cache hit rate and minimise latency and network load. The CS approach achieves this balance by searching the globe and refining locally through the use of Lévy flights. The simulation outcomes, produced under the conditions of Zipf-distributed patterns of requests, demonstrate that the offered solution is always superior to the current approaches to caching. The CS-based system has significant improvements in terms of cache hit ratio, average latency, and overall network efficiency compared to the traditional strategies and probabilistic caching models. Its strength and flexibility are also supported by the convergence and trade-off behaviour analysis. The results indicate that the developed caching framework can be considered a lightweight and scalable alternative to heavy learning-based algorithms, which makes it a viable solution to the content-centric and edge computing environment in the future.

Keywords

Content-Centric Networking, Caching, Cuckoo Search, Lévy flight, Metaheuristic Algorithms, Traditional Strategies, Dynamic Caching, Network Optimization.

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