Optimized private cloud storage for heterogeneous files in an university scenario

File access from different workplaces within an organization is important to reduce the inconsistency of the data among the files. Hence, there is a need for common online drive within the organization. Public cloud storage services or online drives can be used for this purpose. However, there are certain security related issues in using the public cloud storage. Hence, private cloud storage is more suitable for building a common online drive within the campus, as the data is within the firewall of the organization. The data that occupies the private cloud storage can be of different file types such as TXT, PPT, DOC, PDF, RAR, EXE, MP3, AVI, etc. Since the storage space is limited in the private cloud storage, data should be optimally utilized. Towards this objective, deduplication technique has been used. The primary contribution of this paper is to incorporate deduplication for different categories of files. Further, this paper also analyses the unique characteristics of the various categories of files. Based on this analyis, this paper provides a mechanism for selecting suitable chunking and hashing techniques to minimize the computational overhead.