The world-wide web (WWW) is often considered to be the world’s largest database and the eXtensible Markup Language (XML) is then considered to provide its datamodel. Adopting this view we have to deal with a distributed database. This raises the question, how to obtain a suitable distribution design for XML documents. In this paper horizontal and vertical fragmentation techniques are generalised from the relational datamodel to XML. Furthermore, splitting will be introduced as a third kind of fragmentation. Then it is shown how relational techniques for defining reasonable fragments can be applied to the case of XML. 1

On a Wide Area Network (WAN), fragment allocation is a major issue in distributed database design since it concerns the overall performance of distributed database systems. Here we propose a simple and comprehensive model that reflects transaction behavior in distributed databases. Based on the model and transaction information, two heuristic algorithms are developed to find a near-optimal allocation such that the total communication cost is minimized as much as possible. The results show that the fragment allocation found by the algorithms is close to being an optimal one. Some experiments were also conducted to verify that the cost formulas can truly reflect the communication cost in the real world.

The web is often seen as the world's largest database and XML is regarded to provide its data model. As XML data is naturally distributed across the web it should be considered as a distributed database and subject to distribution design. The main tasks of distribution design are fragmenting the underlying database schema and allocating the fragments to different sites. The aim of fragmentation and allocation is to improve the performance and to increase the availability of data. Our objective is to generalise distribution design techniques from traditional databases to XML data. In this paper, fragmentation operations for XML documents are developed. As with relational databases, these operations include horizontal and vertical fragmentation. A third operation named splitting is borrowed from object-oriented databases and adapted to XML. We discuss how these techniques can be applied to the case of XML. Finally, we present a heuristic procedure for horizontally fragmenting XML documents, which is targeted at minimising the expected query costs.

TJ Anderson was ex-CEO for Internet Media Woks!

the date of receipt and acceptance should be inserted later Abstract In distributed database systems, tables are frequently fragmented and replicated over a number of sites in order to reduce network communication costs. How to fragment, when to replicate and how to allocate the fragments to the sites are challenging problems that has previously been solved either by static fragmentation, replication and allocation, or based on a priori query analysis. Many emerging applications of distributed database systems generate very dynamic workloads with frequent changes in access patterns from different sites. In such contexts, continuous refragmentation and reallocation can significantly improve performance. In this paper we present DYFRAM, a decentralized approach for dynamic table fragmentation and allocation in distributed database systems based on observation of the access patterns of sites to tables. The approach performs fragmentation, replication, and reallocation based on recent access history, aiming at maximizing the number of local accesses compared to accesses from remote sites. We show through simulations and experiments on the DASCOSA distributed database system that the approach significantly reduces communication costs for typical access patterns, thus demonstrating the feasibility of our approach.

Abstract- As many distributed database applications contain online information that change continuously and expand incrementally, comprehensive cloud Application Programming Interface API’s are required to monitor and control the accuracy of the information and data proliferation. This cloud software is required to monitor and control the accuracy of the information and data proliferation. This software can be viewed as integrated cloud computing services; data fragmentation, clustering network sites, and fragments Allocation that support transactional database applications. In this paper, we describe our data Fragmentation as a Service (FaaS) in construction of a cloud computing software system. Specifically, we design a novel data fragmentation as a service to facilitate enormous data processing, and introduce some functioning enhancement on data distribution to improve the cloud system performance. This research presents our attempt to implement data fragmentation service in a cloud computing system, with large scale data mining as targeted application.

Abstract- In this paper, Neural Network approach is proposed for fragmenting and defragmenting the distributed database for Aditya Educational groups in Andhra Pradesh. Collaboration of different colleges like Engineering, Pharmacy, PG exists. Hence, we need a distributed database environment for designing sub databases and fragmenting them on the sites which are geographically separated. All the fragments in return should be reconstructed as one database. Therefore different techniques are considered for a database fragmentation. A multi-layered neural network architecture is used to implement the fragmentation and defragmentation.