In this paper, we propose a new class of regular fractional repetition (FR) codes constructed from perfect difference families and quasi-perfect difference families to store big data in distributed storage systems. The main advantage of the proposed construction method is that it supports a wide range of code parameter values compared to existing ones, which is an important feature to be adopted in practical systems. When using one instance of the proposed codes for a given parameter set, we show that the amount of stored data is very close to that of an existing state-of-the-art optimal FR code.
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