CONTENT PUSH ON ICN INFORMATION-CENTRIC-NETWORKING OVER CONTENT CENTRIC SOCIAL NETWORKS

Abstract

In Many people's private lives are being documented and broadcast online because to the proliferation of digital gadgets and the popularity of social networking. One of the most common online activities is content sharing, however this practise is seldom taken into account during the design phase of a website. One well-known use of this architecture is information-centric networking (ICN). Novel networking designs have recently surfaced to handle the quickly changing and emerging Internet use patterns. One well-known use of this architecture is information-centric networking (ICN).  ICN brings up a whole new channel of information exchange optimisation possibilities by seeing content as the fundamental component of networking functions. This study provides a method that enhances ICN's core functionality and makes use of content identification at the network layer, enabling the selective retrieval of parts of material that are already stored in ICN's in-network caches. This idea also makes it possible for information producers to effortlessly offload part of the labour involved in content processing to the network. The observed findings reveal decreased network core traffic and storage use. To solve this problem, we require correct content push, where the primary problems are demonstrating exact descriptions of users and supporting the big data nature of both individuals and contents, which CCN makes possible because to its reduced connection cost and faster download times. Using the named content, CCN allows for real-time interest tracking and encourages us to study novel content in order to push our online learning algorithm to very efficient results in the big data context, where it causes no additional strain on the network and is able to circumvent the cold start problem.