Biblio

The shift from the host-centric to the information-centric paradigm results in many benefits including native security, enhanced mobility, and scalability. The corresponding information-centric networking (ICN), also presents several important challenges, such as closest replica routing, client privacy, and client preference collection. The majority of these challenges have received the research community’s attention. However, no mechanisms have been proposed for the challenge of effective client preferences collection. In the era of big data analytics and recommender systems customer preferences are essential for providers such as Amazon and Netflix. However, with content served from in-network caches, the ICN paradigm indirectly undermines the gathering of these essential individualized preferences. In this paper, we discuss the requirements for client preference collections and present potential mechanisms that may be used for achieving it successfully.

The shift from the host-centric to the information-centric paradigm results in many benefits including native security, enhanced mobility, and scalability. The corresponding information-centric networking (ICN), also presents several important challenges, such as closest replica routing, client privacy, and client preference collection. The majority of these challenges have received the research community’s attention. However, no mechanisms have been proposed for the challenge of effective client preferences collection. In the era of big data analytics and recommender systems customer preferences are essential for providers such as Amazon and Netflix. However, with content served from in-network caches, the ICN paradigm indirectly undermines the gathering of these essential individualized preferences. In this paper, we discuss the requirements for client preference collections and present potential mechanisms that may be used for achieving it successfully.