The phenomenon of data explosion represents a severe challenge for the upcoming big data era.However,the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in redundant content transmission and the end-point-based communication model.Information-centric networking(ICN)is a paradigm for the future Internet that can be utilized to resolve the data explosion problem.In this paper,we focus on content-centric networking(CCN),one of the key candidate ICN architectures.CCN has been studied in various network environments with the aim of relieving network and server burden,especially in name-based forwarding and in-network caching functionalities.This paper studies the effect of several caching strategies in the CCN domain from the perspective of network and server overhead.Thus,we comprehensively analyze the in-network caching performance of CCN under several popular cache replication methods(i.e.,cache placement).We evaluate the performance with respect to wellknown Internet traffic patterns that follow certain probabilistic distributions,such as the Zipf/Mandelbrot–Zipf distributions,and flashcrowds.For the experiments,we developed an OPNET-based CCN simulator with a realistic Internet-like topology. The phenomenon of data explosion represents a severe challenge for the upcoming big data era. However, the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in redundant content transmission and the end-point-based communication model. Information-centric networking (ICN) is a paradigm for the future Internet that can be utilized to resolve the data explosion problem. In this paper, we focus on content-centric networking (CCN), one of the key candidate ICN architectures. CCN has has studied in various network environments with the aim of relieving network and server burden, especially in name-based forwarding and in-network caching functionalities. This paper studies the effect of several caching strategies in the CCN domain from the perspective of network and server overhead .Thus, we comprehensively analyze the in-network caching performance of CCN under several popular cache replication methods (ie, cache placement) .We evaluate the perfo rmance with respect to well known Internet traffic patterns that follow certain probabilistic distributions, such as the Zipf / Mandelbrot-Zipf distributions, and flashcrowds. For the experiments, we developed an OPNET-based CCN simulator with a realistic Internet-like topology.