Information Centric Networking (ICN) is a new paradigm, aimed at shifting to the future Internet from host centric to a content centric approach. ICN focuses on retrieval and dissemination of information between pairwise communications of hosts. Information are organized in the form of Information Objects (IO), known as Named Data Objects (NDO). These NDO are location independent. Objects in ICN are stored in the system overlay; popularly known as Name Resolution System (NRS). NDOs are requested by the Subscribers in the network to get the needed information from the Publishers, through NRS. Thus, the NRS is responsible in forwarding the interest packets based on the names of NDOs. This application of ICN depends on the scalability of the NRS. To design NRS, the most significant issue is scalability due to the ever-increasing number of NDOs. This paper aims to present the issues, by proposing balanced binary tree data structure to organize and store the NDOs. The methodology proposed in this work is thus; for every new insertion in the tree, a Balance Factor (BF) is computed to balance the height of left and right sub-tree. According to our investigation, balanced binary tree provides less searching time when compared to the Distributed Hash Table (DHT) approach. Simulation results show that End-to-End delay decreases by increasing the throughput in the network.