DDAS using Kerberos with Adaptive Huffman Coding to enhance data retrieval speed and security

The increasing fad of deploying application over the web and store as well as retrieve database to/from particular server. As data stored in distributed manner so scalability, flexibility, reliability and security are important aspects need to be considered while established data management system. There are several systems for database management. After reviewing Distributed data aggregation service(DDAS) system which is relying on Blobseer it found that it provide a high level performance in aspects such as data storage as a Blob (Binary large objects) and data aggregation. For complicated analysis and instinctive mining of scientific data, Blobseer serve as a repository backend. WS-Aggregation is the another framework which is viewed as a web services but it is actually carried out aggregation of data. In this framework for executing multi-site queries a single-site interface is provided to the clients. Simple storage service (S3) is another type of storage utility. This S3 system provides an anytime available and low cost service. Kerberos is a method which provides a secure authentication as only authorized clients are able to access distributed database. Kerberos consist of four steps i.e. Authentication Key exchange, Ticket granting service Key exchange, Client/Server service exchange and Build secure communication. Adaptive Huffman method to writing (also referred to as Dynamic Huffman method) is associate accommodative committal to writing technique basic of Huffman coding. It permits compression as well as decompression of data and also permits building the code because the symbols square measure is being transmitted, having no initial information of supply distribution, that enables one-pass cryptography and adaptation to dynamical conditions in data.