Data Grid Concepts for Data Security in Distributed Computing

TL;DR

This paper discusses data partitioning and dynamic replication in data grids to enhance data security, survivability, and access performance in distributed computing environments.

Contribution

It introduces methods for optimal allocation of sensitive data using secret sharing and erasure coding schemes in data grids.

Findings

Improved data security through partitioning and replication.

Enhanced data availability and survivability.

Efficient access performance in distributed systems.

Abstract

Data grid is a distributed computing architecture that integrates a large number of data and computing resources into a single virtual data management system. It enables the sharing and coordinated use of data from various resources and provides various services to fit the needs of high performance distributed and data-intensive computing. Here data partitioning and dynamic replication in data grid are considered. In which security and access performance of a system are efficient. There are several important requirements for data grids, including information survivability, security, and access performance. More specifically, the investigation is the problem of optimal allocation of sensitive data objects that are partitioned by using secret sharing scheme or erasure coding scheme and replicated. DATA PARTITIONING is known as the single data can be divided into multiple objects. REPLICATION is known as process of sharing information. storing same data in multiple systems. Replication techniques are frequently used to improve data availability. Single point failure does not affect this system. Where the data will be secured.