Affinity-Based User Clustering for Efficient Edge Caching in Content-Centric Cellular Networks
| Autor: | Adriana Viriato Ribeiro, Leobino N. Sampaio, Artur Ziviani |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Computer science 05 social sciences 050801 communication & media studies 020206 networking & telecommunications Context (language use) 02 engineering and technology Base station 0508 media and communications 0202 electrical engineering electronic engineering information engineering Cellular network Cache Small cell Enhanced Data Rates for GSM Evolution business Cluster analysis Computer network |
| Zdroj: | ISCC |
| Popis: | Network densification by small cell networks has become the main alternative for mobile network operators to deal with an ever-increasing traffic growth. In this context, Named Data Networking (NDN), an evolution of Content-Centric Networking (CCN), emerges as an alternative to improve data offloading by the promotion of in-network caching. In this paper, we propose a user clustering scheme that takes advantage of the affinity among users with respect to frequency of content requisition and common interest for content for a more efficient edge caching. The proposed strategy is evaluated in a varied set of scenarios, including different cache sizes, communication models, or concentration levels of content popularity. Simulation results show that the proposed strategy increases both cache hit ratio and data offloading in Content-Centric Cellular Networks. |
| Databáze: | OpenAIRE |
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