An Efficient Stochastic Update Propagation Method in Data Warehousing

This article develops a stochastic update propagation method for an operational data store (ODS) in data warehousing (DW) environments where data storage (and retrieval) is required as a sum of data at distributed source nodes. The authors' proposed method results in less network traffic (as compared with the real-time method) due to update propagation required because of changes in source data. More importantly, the method allows system users to place limits on the discrepancy between the source data and the ODS data that could result due to a time lag between source data changes and the update operation. Finally, the pre-specified limits on the discrepancy are maintained while accounting for two crucial factors in distributed systems: 1) some nodes are situated on more congested network links, and 2) some of the links on the network are less reliable. Real-time data propagation does not account for these frequently encountered networking concerns.

Mediation of Lazy Update Propagation in a Replicated Database over a Decentralized P2P Architecture

While replicating data over a decentralized Peer-to- Peer (P2P) network, transactions broadcasting updates arising from different peers run simultaneously so that a destination peer replica can be updated concurrently, that always causes transaction and data conflicts. Moreover, during data migration, connectivity interruption and network overload corrupt running transactions so that destination peers can experience duplicated data or improper data or missing data, hence replicas remain inconsistent. Different methodological approaches have been combined to solve these problems: the audit log technique to capture the changes made to data; the algorithmic method to design and analyse algorithms and the statistical method to analyse the performance of new algorithms and to design prediction models of the execution time based on other parameters. A Graphical User Interface software as prototype, have been designed with C #, to implement these new algorithms to obtain a database synchronizer-mediator. A stream of experiments, showed that the new algorithms were effective. So, the hypothesis according to which “The execution time of replication and reconciliation transactions totally depends on independent factors.” has been confirmed.

An Efficient Stochastic Update Propagation Method in Data Warehousing

This article develops a stochastic update propagation method for an operational data store (ODS) in data warehousing (DW) environments where data storage (and retrieval) is required as a sum of data at distributed source nodes. The authors' proposed method results in less network traffic (as compared with the real-time method) due to update propagation required because of changes in source data. More importantly, the method allows system users to place limits on the discrepancy between the source data and the ODS data that could result due to a time lag between source data changes and the update operation. Finally, the pre-specified limits on the discrepancy are maintained while accounting for two crucial factors in distributed systems: 1) some nodes are situated on more congested network links, and 2) some of the links on the network are less reliable. Real-time data propagation does not account for these frequently encountered networking concerns.

Knowledge Innovation Through Update Propagation in Collaborative Data Sharing Systems

Innovative knowledge discovery comes through collaboration of knowledge in educational systems. In a collaborative educational system the heterogeneity of data in different learning management systems presents many difficulties for data sharing; some of these difficulties are how to integrate data, produce results for user queries, and find the correct data from heterogeneous learning management systems. In the past few years, various educational system architectures have been proposed; however, issues related to sharing data from different systems have been given less attention. Considering the lack of collaboration of knowledge this chapter investigates a problem of sharing of innovative knowledge among collaborative educational institutes. The knowledge is shared by propagation of updates. Updating innovative knowledge is done by propagating update from the originating source to other collaborative partners. The author examines update propagation in both cyclic and acyclic networks. Moreover, the authors considers cases where a source is temporarily unavailable or offline.

Giải pháp hiệu quả đảm bảo nhất quán dữ liệu chia sẻ phân tán trên nền tảng P2P có cấu trúc

There are certain difficulties in ensuring the consistency of data sharing and distribution on structured P2P substrate because of the requirements of simultaneous processing interacted by many users and peer's input/output or updated speed. This paper presents a high effective solution which is proposed for structured P2P substrate, uses the updated dissemination tree and proposes a method using buffer and index vectors in order to "condition" between the requests and processes of updating. The experimental results conducted on Oversim are aimed at comparing the efficiency of new proposed solution with that of Nakashima. The experimental results indicate that the new proposed is highly effective in ensuring the consistency (over 90%) and satisfies the requirements of latency of update propagation. Especially, in case the peer’s input/output or updated speed is high, the new proposed also achieve greater efficiency.