A scalable array storage for efficient maintenance of future data

Array-based storage system employs a renewed interest in the featured applications for their easy maintenance in the context of large volume data. However, the conventional schemes of array storages suffer from lack of scalability for dynamic data as they need to reallocate the whole array if the size of the array limit overflows. Therefore, the conventional array storage is difficult to use when the data grows overtime. To maintain such velocity of the future data, the array storage must be dynamic which can expand the size according to the growing nature of the data. Moreover, the address space of the array-based storage system overflows quickly if the length of dimension and the number of dimension is large. The index array models render dynamic storage system, but retrieval from index array model shows poor performance than the conventional schemes. In this paper, we demonstrate an index array-based scalable array storage that maintains the growing future data during runtime. The key idea is to convert an n -dimensional array into 2 dimensions and organize the array elements into ordered collections called segments. These segments divide the large allocation size into smaller one that delays the address space overflow. The retrieval performance of the proposed scheme outperforms other existing array systems. Since it converts an n -dimensional array into 2 dimensions, and it needs 2 indices only to maintain scalability. Therefore, it reduces the index overhead as well. The scheme also shows improved storage management performance than other approaches.