Information dispersal is a technique in which pieces of data are distributed among various nodes such that the data can be reconstituted from any threshold number of these pieces. Information dispersal algorithms employ a method in which a file F needs to be dispersed among n nodes such that any m pieces will be sufficient to reconstruct the whole file F. The size of each piece is| F/m|. We must also ensure that the complete knowledge of any m-1 pieces is insufficient to reconstruct the complete file F. The ideas for accomplishing this have been given in many literatures in the past. A discussion and comparison of some of these is covered in this chapter.