A Scalable Storage System For Structured Data

Abstract

Array based storage system is a key choice of many featured applications such as Scientific, engineering, and financial computing applications; for their easy maintenance. However, the lack of scalability of the conventional approaches degrades with the Dynamic size of data sets as they entail reallocation in order to preserve expanded data Velocity. To maintain the velocity of data, the storage system must be scalable enough by Allowing subjective expansion on the boundary of array dimension. Again, for an array based storage system, if the number of dimension and length of each dimension of the Array is very high then the required address space overflows and hence it is impossible to Allocate such a big array. We demonstrate a dynamic scalable array storage scheme Namely Scalable Array Indexing (SAl) that can be an efficient choice of large volume Dynamic data management by removing the problems of the existing ones. The SAl converts an n dimensional array to 2 dimensions. Traditionally, the dynamic array models need indices for each dimensions. Since, SAl is a 2 dimensional dynamic model it reduces the index overhead significantly and compromises relatively faster data accessing. We also propose another scalable structure based on the SAl scheme to increase storage utilization. We named the structure as Segment based Scalable Array Indexing (SSAI). Using our SSAI structure, we also offer an efficient encoding with good comparison ratio and range of usability. All the operations are presented with sufficient theoretical analysis and experimental results